Republishing service manual content

One of the many things I did some work on while at GDS back in 2013 was the Government Service Design Manual. This was intended to be a central resource for teams across (and outside) Government about how to go about building, designing and running modern internet-era services. It was a good snapshot of opinions from the people that made up GDS on a wide range of different topics. Especially for the people who spent time in the field with other departments, having an official viewpoint published publicly was hugely helpful.

Recently the Service Manual got a bit of a relaunch but unfortunately this involved deleting much of the content about operations and running a service. Even more unfortunately the service manual is now described as something that:

exists to help people across government build services that meet the Digital Service Standard and prepare for service assessments.

So in basic terms it’s refocusing on helping people pass the exam rather than being all about learning. Which is a shame. Compare that with the original intent:

Build services so good that people prefer to use them

However, all that content is not lost. Luckily the content is archived on GitHub and was published under the terms of the Open Government License which allows for anyone to “copy, publish, distribute and transmit the Information”. So I’m choosing to republish a few of the pieces I wrote and found useful when talking to and assisting other Government departments. These represent an interesting snapshot from a few years ago, but I think mainly stand the test of time, even if I’d change a few things if I wrote them today.

What is Devops?

This post was originally written as part of the Government Service Design Manual while I was working for the UK Cabinet Office. Since my original in 2013 it was improved upon by several others I’m republishing it here under the terms of the Open Government licence.

Devops is a cultural and professional movement in response to the mistakes commonly made by large organisations. Often organisations will have very separate units for:

  • development
  • quality assurance
  • operations business

In extreme cases these units may be:

  • based in different locations
  • work for different organisations
  • under completely different management structures

Communication costs between these units, and their individual incentives, leads to slow delivery and a mountain of interconnected processes.

This is what Devops aims to correct. It is not a methodology or framework, but a set of principles and a willingness to break down silos. Specifically Devops is all about:

Culture

Devops needs a change in attitude so shared ownership and collaboration are the common working practices in building and managing a service. This culture change is especially important for established organisations.

Automation

Many business processes are ready to be automated. Automation removes manual, error-prone tasks – allowing people to concentrate on the quality of the service. Common areas that benefit from automation are:

  • release management (releasing software)
  • provisioning
  • configuration management
  • systems integration
  • monitoring
  • orchestration (the arrangement and maintenance of complex computer systems)
  • testing

Measurement

Data can be incredibly powerful for implementing change, especially when it’s used to get people from different groups involved in the quality of the end-to-end service delivery. Collecting information from different teams and being able to compare it across former silos can implement change on its own.

Sharing

People from different backgrounds (ie development and operations) often have different, but overlapping skill sets. Sharing between groups will spread an understanding of the different areas behind a successful service, so encourage it. Resolving issues will then be more about working together and not negotiating contracts.

Why Devops

The quality of your service will be compromised if teams can’t work together, specifically:

  • those who build and test software
  • those that run it in production

The root cause is often functional silos; when one group owns a specific area (say quality) it’s easy for other areas to assume that it’s no longer their concern.

This attitude is toxic, especially in areas such as:

  • quality
  • release management
  • performance

High quality digital services need to be able to adapt quickly to user needs, and this can only happen with close collaboration between different groups.

Make sure the groups in your team:

  • have a shared sense of ownership of the service
  • have a shared sense of the problem
  • develop a culture of making measurable improvements to how things work

Good habits

Devops isn’t a project management methodology, but use these good habits in your organisation. While not unique to Devops, they help with breaking down silos when used with the above principles:

  • cross-functional teams – make sure your teams are made up of people from different functions (this helps with the team owning the end-to-end quality of service and makes it easier to break down silos)
  • widely shared metrics – it’s important for everyone to know what ‘good’ looks like so share high and low level metrics as widely as possible as it builds understanding
  • automating repetitive tasks – use software development to automate tasks across the service as it:
    • encourages a better understanding of the whole service
    • frees up smart people from doing repetitive manual tasks
  • post-mortems – issues will happen so it’s critical that everyone across different teams learns from them; running post-mortems (an analysis session after an event) with people from different groups is a great way of spreading knowledge
  • regular releases – the capacity for releasing software is often limited in siloed organisations, because the responsibilities of the different parts of the release are often spread out across teams – getting to a point where you can release regularly (even many times a day) requires extreme collaboration and clever automation

Warning signs

Like agile, the term Devops is often used for marketing or promotional purposes. This leads to a few common usages, which aren’t necessarily in keeping with what’s been said here. Watch out for:

  • Devops tools (nearly always marketing)
  • a Devops team (in many cases this is just a new silo of skills and knowledge)
  • Devops as a job title (you wouldn’t call someone “an agile”)

Further reading

Agile and IT service management

This post was originally written as part of the Government Service Design Manual while I was working for the UK Cabinet Office. Since my original in 2013 it was improved upon by several others I’m republishing it here under the terms of the Open Government licence.

The Digital by Default standard says that organisations should (emphasis on operate added):

Put in place a sustainable multidisciplinary team that can design, build and operate the service, led by a suitably skilled and senior service manager with decision-making responsibility.

This implies a change to how many organisations have traditionally run services, often with a team or organisation building a service separate from the one running it. This change however does not mean ignoring existing good practice when it comes to service management.

Agile and service management

The principles of IT service management (ITSM) and those of agile do not necessarily conflict – issues can arise however when organisations implement rigid processes without considering wider service delivery matters, or design and build services without thinking about how they will be operated.

The agile manifesto makes the case for:

  • Individuals and interactions over processes and tools
  • Working software over comprehensive documentation
  • Customer collaboration over contract negotiation
  • Responding to change over following a plan

It is too easy to position service management as opposed to agile as traditional service management practices can be viewed as focusing on processes, tools, documentation, planning and contract negotiation – the items on the right hand side of the points above.

However, the agile manifesto goes on to say:

That is, while there is value in the items on the right, we value the items on the left more.

To build and run a successful service you will need to work on suitable processes and manage third party relationships. Using existing service management frameworks (especially as a starting point) is one approach to this problem.

ITIL

ITIL (the Information Technology Infrastructure Library) is one such framework. ITIL does a particularly good job of facilitating shared language. For instance it’s definition of a service is:

A service is a means of delivering value to customers by facilitating outcomes customers want to achieve.

The current version of ITIL currently provides 5 volumes and 26 processes describing in detail various aspects of service management:

Service Strategy

  • IT service management
  • Service portfolio management
  • Financial management for IT services
  • Demand management
  • Business relationship management

Service Design

  • Design coordination
  • Service Catalogue management
  • Service level management
  • Availability management
  • Capacity Management
  • IT service continuity management
  • Information security management system
  • Supplier management

Service Transition

  • Transition planning and support
  • Change management
  • Service asset and configuration management
  • Release and deployment management
  • Service validation and testing
  • Change evaluation
  • Knowledge management

Service Operation

  • Event management
  • Incident management
  • Request fulfillment
  • Problem management
  • Identity management

Continual Service Improvement

Functions

ITIL also describes four functions that should cooperate together to form an effective service management capability.

  • Service operations
  • Technical management
  • Application management
  • Operations management

The importance of implementation

The above processes and functions make for an excellent high level list of topics to discuss when establishing an operating model for your service, whether or not you adopt the formal methods. In many cases if you have well understood, well established and well documented processes in place for all of the above you should be in a good position to run your service.

When looking to combine much of the rest of the guidance on the service manual with ITIL or other service management frameworks it is important to challenge existing implementations. This is less about the actual implementation and more often about the problems that implementation was designed to originally solve.

An example – service transition

As an example ITIL talks a great deal about Service Transition – getting working functionality into the hands of the users of the service. This is a key topic for The Digital Service Standard too which says that teams should:

Make sure that you have the capacity and technical flexibility to update and improve the service on a very frequent basis.

GOV.UK for instance made more than 100 production releases during its first two weeks after launch.

This high rate of change tends to challenge existing processes designed for a slower rate of change. If you are releasing your service every month or every 6 months then a manual process (like a weekly or monthly in-person change approval board or CAB) may be the most suitable approach. If you’re releasing many times a day then the approach to how change is evaluated, tested and managed tends towards being more automated. This moves effort from occasional but manual activities to upfront design and automation work. More work is put in to assure the processes rather than putting all the effort into assuring a specific transition.

Service management frameworks tend to acknowledge this, for instance ITIL has a concept of a standard change (something commonly done, with known risks and hence pre-approved), but a specific implementation in a given organisation might not.

Other frameworks exist

It is important to note that other service management frameworks and standards exist, including some that are of a similar size and scope to ITIL:

Many organisations also use smaller processes and integrate them together. The needs of your service and organisation will determine what works best for you.

Problematic concepts

Some traditional language tends to cause some confusion when discussing service management alongside agile. It’s generally best to avoid the following terms when possible, although given their widespread usage this isn’t always possible. It is however worth being aware of the problems these concepts raise.

Projects

Projects tend to imply a start and an end. The main goal of project work is to complete it, to reach the end. Especially for software development the project can too often be viewed as done when the software is released. What happens after that is another problem entirely – and often someone else’s problem.

However when building services the main goal is to meet user needs These needs may change over time, and are only met by software that is running in production and available to those users.

This doesn’t mean not breaking work down into easily understandable parts, but stories, sprints and epics are much more suited to agile service delivery.

Business as usual

The concept of business as usual also clashes with a model of continuous service improvement. It immediately brings to mind before and after states, often with the assumption that change is both much slower and more constrained during business as usual. In reality, until you put your service in the hands of real users as part of an alpha or beta you won’t have all the information needed to build the correct service. And even once you pass the live standard you will be expected to:

continuously update and improve the service on the basis of user feedback, performance data, changes to best practice and service demand

Further reading

User stories for web operations teams

This post was originally written as part of the Government Service Design Manual while I was working for the UK Cabinet Office in 2013. I’m republishing it here under the terms of the Open Government licence.

This document outlines the typical scope of infrastructure and web operations (sometimes erroneously referred to as hosting) work on a large service redesign project.

The sample list of user stories provided is not intended to be a complete list of all areas of interest nor are you likely to need to do all of this for every service. The idea is for this list to be a good starting place from where to you can write additional stories, delete ones you do not require and split stories into smaller ones. Importantly you also need to provide your own acceptance criteria specific to the needs of your service.

Remember these stories are a placeholder for a conversation. For some contexts, that conversation will be ‘this does not apply to my service’ – that is fine. But there will almost certainly be other stories not listed here which do apply.

The problem

An issue we have observed on a number of projects is a lack of understanding early on in a project about the work required to run a large online service. Often this is placed under hosting and is investigated too late in the process.

Intended audience

The hosting of a complex and sensitive software application requires a team of people with specialist skills to design, setup and operate. Because this work is generally not user facing and can be highly technical it is sometimes easy to leave until later – with potentially dire consequences for launching safely and on time.

Service managers

Does your team have people who deeply understand this topic? If you are not an expert then it is important to involve people permanently in the team who are. They can explain the technical trade offs and decisions which may affect your service.

Delivery managers

As well as understanding the potentially large scope of work, many of the areas discussed here have lead times associated with third parties. The earlier stories related to these topics are brought into project backlogs the sooner estimates can be made and deadlines understood.

Stories

The following stories are intended to provide a starting point for any project, rather than be a complete set. Individual projects would be expected to take and modify stories as needed and importantly to apply their own acceptance criteria specific to their requirements.

The majority of these stories are from the point of view of developers, web operations engineers and the responsible service manager. Although not ideal, for this particular technical topic this works reasonably well. Feel free to change the focus when using them in your backlog.

Process

Development process
As a developer working on the service
So that we can ensure a high level of quality
And so we can maximise the integrity of the source code
I want a well documented and understood development process

Out-of-hours support
As the service manager responsible for the service
So that we can ensure a suitable level of availability and integrity
I want to understand the requirement for Out-of-hours support

Disaster recovery
As the service manager responsible for the service
So that in the event of a disaster everyone doesn’t panic and make things up
I want a clear disaster recovery plan in place to deal with different types of catastrophic event

Release process
As the service manager responsible for the service
So that the service can be changed on a very frequent basis
And so that changes do not cause problems for users
I want a well documented and understood release process

Security response
As the service manager responsible for the service
So that security incidents are handled with extra care
And so that the service meets its wider Government obligation to GovCert
I want a well documented and understood security incident process

Helpdesk
As the service manager responsible for the service
So that communication with users is done in a joined up way
I want a central helpdesk function to deal with events, incidents and requests

Request Management
As the service manager responsible for the service
So that questions from users can be dealt with efficiently
I want a clear information request management policy

Event Management
As the service manager responsible for the service
So that likely events that could affect the running of the service can be dealt with smoothly
I want a clear event management policy

Incident Management
As the service manager responsible for the service
So that problems that arise with that service can be dealt with efficiently
I want a clear incident management policy

Operations manual
As the service manager responsible for the service
So that information about the running of the service is not kept in individuals’ heads
And so information is readily available to people running the service
I want a single place to store content for a service operations manual

Shared service

Source code hosting
As a developer working on the service
So we have somewhere to securely store our source code
I want access to a central source code hosting service or repository

Continuous Integration
As a developer working on the service
So we can ensure a high level of quality in the code
And so we can minimise the time needed for regression testings
I want a Continuous Integration environment which automatically runs tests against every commit

External DNS
As a web operations engineer
So that visitors to the service don’t need to remember an IP address that will change
I want a process and supplier relationship to manage external DNS addresses

Policy

Sensitivity of source code
As a developer working on the service
So that I understand the controls that need to be in place
And so that I know who and how I may share it
I want a clear policy around the sensitivity of source code

Third party code
As a developer working on the service
I want a clear policy around use of third party source code libraries
So that I do not introduce unknown security problems

Change evaluation
As the service manager responsible for the service
So that I can release changes to production quickly
And so that we can meet our obligation to the Digital by Default Service Standard
I want a documented process for evaluating and deciding on a change to the production service

Access control
As the service manager responsible for the service
So that the confidentiality, integrity and availability of the service isn’t compromised
And so that suitable technical controls can be put in place to enforce it
I want a clear policy on who has access to what on the production system

Separation of duties
As the service manager responsible for the service
So that we can ensure the service has enough people in the right roles
I want to understand any required separation of duties (whether driven by legislation or security concerns)

Clearances
As the service manager responsible for the service
So that security clearances can be arranged early in the project to avoid access restrictions later on
I want to know what level of clearances are required for different roles (including third parties)

Releasing open source
As a developer working on the service
So that I do not introduce unknown security problems
And so that we can meet our obligation to the Digital by Default Service Standard
I want a clear policy around releasing code as open source

Design

Government networks
As a technical architect
So that the right suppliers are contracted
And so that long lead times are factored into the project plan early
I want to know whether the service requires access to a Government network like the PSN or GSI

Multiple infrastructure providers
As the service manager for this service
So that I understand the intended availability constraints
I want to know whether multiple suppliers of Infrastructure are required

Capacity planning
As a web operations engineer
So that we can estimate the number and size of infrastructure components (instances, firewalls, load balancers etc.)
And so that resource based costs can be estimated
I want to carry out some capacity planning activities

Network architecture
As a technical architect
So that I can build out a production environment to an agreed specification
I want a network architecture design

Components

Web servers
As a web operations engineer working on the service
So that we can serve HTTP request
And so we can proxy requests to application servers
I want to install and configure a web server

Databases
As a web operations engineer working on the service
So that data can be stored in a manner befitting its structure
And so the stored data can be queried as quickly as required
I want to install and configure a suitable database server

As a web operations engineer working on the service
So that data can still be read even during a failure of a single database server
I want to configure some failover or other redundancy mechanism for the database

As a web operations engineer working on the service
So that data can still be written even during a failure of a single database server
I want to configure some failover or other redundancy mechanism for the database

Load balancers
As a web operations engineer working on the service
So that web requests can still be served even with the failure of one or more web servers
I want to install and/or configure a load balancer

Internal DNS
As a web operations engineer working on the service
So that we can easily address our services and instances
I want to install and/or configure a mechanism to manage internal DNS

Database backups
As the service manager for the service
So that we can recover from a large failure of our database infrastructure
I want regular automated backups to be taken of the data stored in the database

As the service manager for the service
So that we can recover from a large failure of a single suppliers infrastructure
I want regular automated backups to be stored off site

HTTP cache
As a web operations engineer working on the service
So that the service remains fast when serving identical content
And so load is minimised on the application servers
I want to install an HTTP cache

Email gateway
As a developer working on the service
So that the service can send email to administrators or end users
I want to setup and configure a suitable email gateway

Application servers
As a developer working on the service
So that the code I write can be run on server instances
I want to install and configure a suitable application server

Internal package repository
As a web operations engineer working on the service
So that we can use software not available in our operating system repositories
And so that we can use the security, dependency management and versioning features
I want to install and configure an internal package repository

Artifact repository
As a developer working on the service
So that we can share and version individual code components that need it
I want to install and configure an artifact repository

Message queue
As a developer working on the service
So that I can easily and efficiently process work asynchronously
I want to install and configure a suitable message queue or work queue system

Search server
As a developer working on the service
So that I can quickly and efficiently search through large amounts of data
I want to install and configure a suitable search engine

Object cache
As a developer working on the service
So that I can minimise the number of queries to the database
And so that I can keep the service fast and responsive to users
I want to install and configure a object caching system

Monitoring

Metric collection service
As a web operations engineer working on the service
So that we can collect large numbers of time series metrics from the running service
I want to install and configure a metric collection system

Application running monitoring checks
As a web operations engineer working on the service
So that we can run checks against metrics from the metrics system
And so that we can run active checks based on arbitrary code
I want to install and configure a monitoring system

Smoke tests
As a developer working on the service
So that I know that I haven’t broken anything when deploying my application
I want a series of smoke tests to be run after all deployments

Application metrics
As a developer working on the service
So that I can gain visibility of how my application is running in production
And so we can find and fix problems with it quickly
I want a simple way of instrumenting my application to feed metrics to the metrics system

System metrics
As a web operations engineer working on the service
So that we can identify and fix problems with the system, ideally before they occur
I want to set up collection of low level system metrics like load, disk, network io, etc.

Security monitoring
As a web operations engineer working on the service
So that we notice quickly and are alerted to any incidents with a security flavour
I want to configure suitable security monitoring tools

Notifications
As a web operations engineer or developer supporting the service
So that I know about any issues as they happen
I want to set up suitable notifications from the monitoring system

Transactional monitoring
As a developer working on a transactional service
So that we can block fraudulent or otherwise suspect transactions
I want to install and configure a transactional monitoring system with suitable rules

External monitoring
As the service manager for the service
So that in the event of a failure of the monitoring system
And so that the service is monitoring from outside our local network
I want an external monitoring capability with basic checks to monitoring service uptime

Monitoring data feed from infrastructure provider
As a web operations engineer working on the service
So that I am aware of problems in the hypervisor, physical or network infrastructure
I want a feed of monitoring data from the Infrastructure supplier

Logging

Log collection
As a web operations engineer working on the service
So that I can easily see everything that is happening in specific applications
I want to collect all the logs from applications running on the same host in one place

Log aggregation
As a web operations engineer working on the service
So that I don’t have to go to an individual machine to view its logs
I want all logs from all machines to be aggregated together

Log storage
As a web operations engineer working on the service
So that logs can be kept for a suitable period of time
I want to provision enough storage for log archiving

Log viewing
As a web operations engineer working on the service
So that I can see what is happening across the infrastructure
I want a mechanism for viewing and searching logs in as near real time as possible

As a developer working on the service
So that I can extract information from logs to aid with improving the service
I want a mechanism to run queries across the aggregated logs

Configuration management

Configuration management client
As a web operations engineer working on the service
So that changes to server configuration can be made safely and quickly
I want to install software to manage configuration management

Configuration management database
As a web operations engineer working on the service
So that configuration changes are tracked over time
And so that current state of available to query
I want to install software to manage a configuration management database

Configuration management server
As a web operations engineer working on the service
So that all nodes do not have all configuration information
I want to install software to allow centralised management of Configuration management code

Deployment

Configuration management code deployment mechanism
As a web operations engineer working on the service
So that configuration changes can be made safely and in an auditable manner
I want a deployment process and tooling for configuration management code

Application deployment mechanism
As a developer working on the service
So that changes to applications can be made available to users
And so that changes are made in a safe and auditable manner
I want a deployment process and tooling for application code

Release tracking
As the service manager for the service
So that we have an auditable log of what was changed when by whom
I want an up-to-date list of releases to be maintained

Packaging
As a web operations engineer working on the service
So that we don’t have to compile customised applications from source before using them
And so we can take advantage of dependency and version management capabilities of the OS
I want a process and tooling for creating our own system packages

Orchestration
As a web operations engineer working on the service
So that I can run commands across multiple instances quickly
I want tooling in place which allows some orchestration based on the current instances

Database migrations
As a web operations engineer working on the service
So that I can have confidence that database migration scripts will work when applied to production
I want database migrations to be deployed through the same sequence of environments as code changes

Management of secrets
As a web operations engineer working on the service
So that I can ensure confidential communication between particular parts of the system
I want a process or tool for managing secrets such as keys and passwords

Access control

End user devices
As the service manager responsible for the service
So that management access to the infrastructure can be locked down to prevent unauthorised access
I want to know what kind of protection the management end user devices require

User directory
As a web operations engineer
So that we do not have to maintain multiple lists of privileged users
And so that users can be added and removed once in a central fashion
I want to install and configure something to provide a single user directory

Key based authentication
As a web operations engineer
So that we are not vulnerable to password based login attempts to individual servers
I want to set-up public key based authentication

Single sign-on
As a web operations engineer
So that any third party web interfaces we use can be accessed via a single login
I want to install and configure a single sign-on systems

Network/VPN configuration
As a web operations engineer
So that management functions can not be accessed via the public internet
And so that we reduce the surface area for attack
I want to restrict management access to a VPN and/or non-public restricted network

Provisioning

Other environments
As the service manage for the service
So that I can see the very latest working version of the service at any time
And so I can share that with people in and outside the team
I want a preview environment to be provisioned which is similar to production

As a web operations engineer working on the service
So that the we have a clean environment in which to test production deployments
And so that we have a secure environment to test with production-like data
I want to provision a staging environment which mimics production as closely as possible

Production environment
As a web operations engineer working on the service
So that the service can launch to the public
I want to provision a production environment

Base image(s)
As a web operations engineer working on the service
So that all server instances start out with sensible security settings
I want to create a base image running the chosen operating system with hardened configuration

Public network interfaces
As a web operations engineer working on the service
So that the application only receives wanted traffic from the internet
And so that we don’t accidentally expose sensitive or insecure components of the system
I want to configure and test the public network interfaces for the system

Private network configuration
As a web operations engineer working on the service
So that individual internal components can only talk with known parts of the system
And so we limit the extent of any security breach
I want to configure and test the private network interfaces for the system

Network codes of connection
As a web operations engineer working on the service
Given I need to communicate with a system only available on a Government network
So that the two systems can talk with each other
I want to meet the code of connection requirements and configure access to the network

Management network
As a web operations engineer working on the service
So that network traffic used to manage the infrastructure is separate from public traffic
And so we can monitor irregularities in network traffic separately
I want to configure a separate management network

Platform load balancers
As a web operations engineer working on the service
So that we can reduce the number of single points of failure
And so that we can scale out to deal with a large amount of traffic
I want to provision load balancers to distribute traffic between multiple instances

Platform firewalls
As a web operations engineer working on the service
So that unwanted traffic can be filtered before it enters our virtual infrastructure
I want to configure the external facing IaaS firewalls to only allow certain traffic

Dynamic environments
As a web operations engineer working on the service
So that we are not constrained by a fixed number of environments
And so we can easy run full stack tests or experiments
I want to be able to easily provision an environment running the full service

Elastic scaling
As a web operations engineer working on the service
So that the service can automatically deal with unexpected increases in traffic
I want to configure tooling to automatically scale the number of instances based on load

Security controls

Operating system hardening
As a web operations engineer
So that we are making use of built-in operating system security controls
I want to automate a default set of hardening rules for our chosen operating system

Malware detection
As a web operations engineer
So that instances which may be compromised can be dealt with quickly
I want to automate the detection of potential malware

Intrusion detection
As a web operations engineer
So that instances which are being attacked or probed can defend themselves
I want to configure an intrusion detection and prevention system

Virus scanning
As a web operations engineer
So we can be sure that files in the system don’t have viruses
I want to install virus scanning for files passing a network boundary

Host firewalls
As a web operations engineer
So that the surface area for attack is limited
And so that services which should only be available locally aren’t exposed on the internet
I want to install and configure a local firewall

On instance event auditing
As a web operations engineer
So that I know when things like logins or other sensitive events happen on instances
I want to set-up some auditing of events

Rate/connection limiting
As a web operations engineer
So that large spikes in traffic from a single source don’t overwhelm application
I want to configure some level of rate and connection limiting for web requests

Secure storage of key material
As a web operations engineer
So that any highly sensitive cryptographic keys are not lost, resulting in a compromise
I want to have a mechanism in place to securely store key material

Third party DDoS protection
As a web operations engineer
So that a the site does not go down under a denial of service attack
I want to purchase and/or configure a level of DDoS protection

Testing

Performance testing
As the service manager responsible for the service
So that we know the service will be fast and responsive under realistic traffic
I want to be able to run a comprehensive performance test suite against the service

As a developer working on the service
So that we know changes to the code do not negatively affect performance
I want the performance test suite to run as part of the continuous integration system

Load testing
As the service manager responsible for the service
So that we know the service will still be working under larger amounts of traffic than are expected
I want to be able to run a comprehensive load test suite against the service

Application penetration testing
As the service manager responsible for the service
So that the service does not get compromised due to a vulnerability
And so we meet our accreditation obligations
I want to run a suitable number of penetration tests against the applications under development

As the service manager responsible for the service
So that the service does not get compromised due to a vulnerability
And so we meet our accreditation obligations
I want to run a suitable number of penetration tests against third party installed applications used as part of the service

Infrastructure penetration testing
As the service manager responsible for the service
So that the service does not get compromised due to a vulnerability
And so we meet our accreditation obligations
I want to run a suitable number of penetration tests against the infrastructure configuration

Operating system

Operation system selection
As a web operations engineer working on the service
So that we have a clear path to receiving security updates
And so we can more easily find support for our systems
I want to select and install a suitable default operating system for the service

File systems
As a web operations engineer working on the service
So that we get the best possible performance and reliability from the disk
I want to select a suitable file system and partition layout

Resource isolation
As a web operations engineer working on the service
So that noisy applications cannot affect other applications on the instance
I want to be able to isolate running applications from each other in terms of memory and CPU

Read-only file systems
As a web operations engineer working on the service
So that I can protect against files being changed due to compromises in the application
I want to be able to configure a read-only file system if appropriate.

Working for a software vendor

One of the reasons I moved to Puppet two and a bit years ago was because I was interested in the software industry. In particular I was interested in being on the vendor side for a while. My background is mainly as a service provider, software as a service, in-house developer/ops type person. This has definitely been an interesting experience, but I’ve not tried too much to explain why, until now.

First, what do we mean by vendor?

a person or company offering something for sale, especially a trader in the street.

So in the context of a software vendor we specifically mean:

a person or company offering software for sale

Note that we’re selling the software, not access to some service provided by software (ie. SaaS). SaaS and other as-a-service models are growing part of the industry, but the business model, development cycle, company structure and other aspects are quite different in my experience, though lots of hybrid models exist too.

Economics and scale

One of the interesting aspects of the software vendor world is the economics, the revenues, and the fact lots of companies are public. This in turn means a large amount of VC money goes into trying to create another large software vendor, because the potential payout is huge.

Take a sample set of companies from the last 10 years or so that are still private: Docker, Puppet, Chef, MongoDB, Elastic, CoreOS, Mesosphere, Weave, Cloudera, etc. Somewhat biased towards my own interests I’ll admit.

Now take a sample of large, public, software vendors: Oracle, Microsoft, CA, SAP, Sage, BMC, VMware. Not counting companies like Intel, Cisco, IBM, Dell (no longer public), and HP with huge software portfolios.

Let’s pick on Sage, a UK software company selling accounting software. As of 2014 Sage had 1169 people in software development R&D roles and they made $1.6billion from software and related services in 2015. That’s probably about the (order of magnitude) number of people employed in R&D roles in the above private softare companies. The revenue is (and I’m guessing here) a bit higher at Sage than those companies combined too. SAP is an order of magnitude larger, both in terms of people (18908 in 2014) and revenues ($18billion also in 2014). Oracle revenues were $38billion as another data point.

So all the cool (or not so cool) companies from the past 10 years or so are a rounding error to the size of the industry. But you wouldn’t know that from reading Hacker News or other parts of the internet. This disconnect is a constant source of interest to me as I spend time with Puppet customers and with the wider infrastructure community at conferences and the like.

A world of difference

My gut feeling is that most people working as software developers, designers, product managers, etc. don’t work for software vendors. Apart from maybe in localised areas like Silicon Valley. But because of the mentioned money and scale (and PR spend) of the big players a great deal of press interest centers around vendors. Docker is probably the best current example of this but it’s more general than one company. This makes what happens in software-vendor-startup-land more visible to everyone else than, say, IT reality in large financial companies.

At the heart of a good software company is a product being built and maintained by a team of engineers, designers, managers, etc. In many ways this is similar to lots of peoples experience of building software (whether at work or at home as part of one open source project or another). But the support surrounding this tends to vary greatly from other areas. A dedicated marketing and product marketing team, dedicated sales staff, a professional services function, training, documentation, public relations personell are all required to turn the software into revenue. And importantly these teams have to work closely together, and be actively involved with the development of the product.

This is very different from an in-house development position, but it’s also quite different from most SaaS operations. SaaS tends (generalising here) to be based around large numbers of individual users with monthly recurring revenues of 10s or 100s of US dollars. Software vendors selling to large enterprises tends to be looking at single large deals of 10s of thousands to many millions of dollars. This tends to mean large differences in total number of customers, revenue per customer, time needed to close a deal, requirement for staff local to a customer, etc. All of that makes for a very different operation and feedback cycle.

Some interesting observations

Software has a much longer shelf-life in the real-world than people typically think on the internet. Take the datacenter automation market. This IDC report for example pegs the market at $2.3billion in 2015. VMware takes the lions share with roughly 30%, with BMC with 10%. For reference Puppet has 3.2% and Chef 1.2%. Obviously this is just one report, and it’s now a year old, but it’s an interesting data point. And compare that to what you might expect if you just follow the software rather than the market. Even in 2015 some people would have been saying “surely everything is Docker and Kubernetes now?“. The reality is closer to it being all shell scripts and BladeLogic for the majority of IT shops.

For the most part, innovators (and some early adopters) don’t buy software, instead they build or co-opt it. Take Netflix, Uber, Amazon, Google, Facebook or similar. All are well-known for building much of there core software and infrastructure and using open source solutions for much of the rest. And it’s not just software, all of the above also have large internal investments in bespoke hardware as well. So who buys software from software vendors? Taking the Rogers’ Innovation Adoption Curve it’s the early majority, the late majority and laggards. That’s ~85% of the market. Most of the noise on the internet about software is from innovators and early adopters, or people who want to be in those groups. But most of the software sold is to people with very different wants and needs. This chasm explains much of the frustration experienced with software, and the difficulty of building software for often very different types of users at the same time.

Much of the writing about continuous delivery and continuous deployment assumes you’re releasing a web site or at least a central, single, service. At the very least this is most peoples experience and context. But shipping software than people install and run themselves tends to make software deployment a pull rather than a push. A vendor can release a new version, but how to make the customer upgrade? Technically this could be reasonably straightforward (Chrome auto-updates for example) but for expensive, often critical, systems in sometimes regulated or otherwise controlled or low trust environments, this turns out to be trickier and more about people than just technology. This is an entire topic on it’s own so I’ll leave it there for now.

Continuous integration for packaged software (true for some, but not most, projects outside software vendors) tends to hit a permutation explosion quite quickly. Take server software because that’s what I’m most familiar with. You’ll definitely support the latest version of RHEL, plus probably a few older versions, and maybe Centos and some of the other variants (Oracle Linux, Scientific Linux) as well. Ubuntu LTS releases probably makes the list, as might Debian stable. You’ll also likely want to test on at least Windows Server 2016 and 2012. You may have need to keep going and support BSD, AIX, HP-UX, SUSE, etc. Puppet has an unreasonably long list of supported and tested platforms for instance. Throw in other variations or configurations or architectures and you have a serious CI environment. Compare this to a more typical case of a deployment pipeline to a single known operating system and version on a server you control.

Open source

One of the notable things about the lists above of older (public) and newer (currently private) software companies is that all of the newer ones are based around an open source software product or products. We’ve had companies based around open source for a long time, but very few make it to the public markets (where we get data to see if they actually work as companies). A recent exception is Hortonworks (HDP) which opened at $26.38 in December 2014 but is down to $8.31 as of this writing, with revenues around $40million a quarter. Red Hat (RHT) did $2billion in 2016 (which remember is 5% of Oracles revenues, but still a large amount).

So undoutedly open source has had a large effect on the software industry as a whole. But the impact on the public markets to date is minimal in terms of new companies. It will be super interesting to see if in 5 years time the list of public software companies based on open source software is larger than it is today.

Conclusions

I mainly wrote this post so I had something to reference when I talk to people about the software industry, and in particular what it’s like working for a software vendor. Speculating about or second guessing one vendor or another is an internet sport (non-more-so than for those that work at other vendors) but from the outside it’s worth an appreciation of some of the differences I think and a bit of empathy for the decisions made. And if the above makes you think this all sounds rather interesting then you’d be right.

The coming of the Kubernetes distributions

Very few people today start using Linux by downloading the linux kernel and starting from scratch. Most people start with a Linux distribution; for instance Debian, Ubuntu or CentOS. These distributions provide some opinions, some central infrastructure, a brand, strong versioning for the entire ecosystem and a bunch of other things. I posit that we’ll see the same pattern emerge with Kubernetes.

What even is Kubernetes?

I’ve seen Kubernetes described as all of the following:

  • An operating system for your datacenter
  • The distributed systems toolkit
  • The Linux kernel for distributed systems

I think all of these descriptions point to the developers intent that Kubernetes is something to build upon, rather than a simple out-of-the-box experience. It’s predominantly about building agreement on the primitives/APIs of distributed systems.

A name for a thing

I’ve not seen much discussion of this in general yet, I think because it’s early days and many of the people looking at Kubernetes today are either developers or early adopter types. These people have been “downloading the kernel and starting from scratch”, even until recently most likely running from source downloaded directly from GitHub. If the Kubernetes ecosystem is to grow then that’s not how more mainstream IT will adopt Kubernetes.

The reason for discussing this now is that I think a name is useful. That way we can talk about Kubernetes (singular, the software) separate from distrubutions of Kubernetes (many of them, from different vendors and communities). I’d be happy to see a different name, but I think distribution probably fits best.

Any evidence?

Absolutely. A range of software vendors are providing what I’m calling Kubernetes distributions. Here is a sample, I’m sure there are and will be more. I’m also sure over time some will disappear or maintain only a niche audience.

  • OpenShift from Red Hat
  • Tectonic from CoreOS
  • Kismatic from Apprenda
  • Rancher
  • Canonical Distribution of Kubernetes
  • GKE from Google
  • Azure Container Service from Microsoft
  • Photon Platform from VMware
  • Navops from Univa

Note that Canonical are already using the term distribution in the name. I’ve seen it used in passing in CoreOS, OpenShift and Apprenda press materials too.

What can we expect from Kubernetes distributions?

Running with the analogy that Kubernetes is “an operating system for your datacenter” and that we’ll have a range of competing Kubernetes distributions, what else can we expect over the next few years?

Package repositories (aka. app stores)

One of the things provided by the traditional Linux distributions has been a central package repository. Most of the packages you’re installing from apt or yum are coming from that currated set of available packages. Not to mention community efforts like EPEL. We already have two package concepts within the Kubernetes ecosystem - container images (often from Docker Hub today, or from internal repositories) and Charts, part of the Helm package management tool (now a CNCF project).

In the short term expect the shared public Charts repository and Docker Hub to dominate. But over time different vendors will launch there own repositories. Partly this will be about building a trusted ecosystem, partly about limiting permutations for support and testing, and partly about control. The prize here is to be “the enterprise app store” and no vendor in this space isn’t going to at least try to own that as part of their platform.

Kubernetes standards and compliance

In an environment with many distributors of core software, it’s common for people to emphasise portability. As vendors extend their distribution (to provide higher level, but potentially proprietary features) this can become muddier. Some level of certification is often the answer. See CloudFoundry or OpenStack for recent examples. Kubernetes is already part of the CNCF, part of the Linux Foundation. I’d expect to see the works standards and certification eventually float around, but my guess is not in the short term.

A fight over who is the most open

Much of the container conversation recently has centered around a weaponisation of open. I think as the different distributions try and take the community with them at the same time as trying to scale sales this will continue. This will be an irritation and is probably best avoided.

Pressure for AWS to offer Kubernetes as a service

I would presume AWS has a very good idea of how many people are actually using Kubernetes on it’s platform. I think as that grows, and as other vendors efforts mature, they will come under pressure to offer the Kubernetes API as a service. I’m still split on whether that will actually happen but that’s a longer blog post about economics.

Differentiating features

Ultimately vendors will try and differentiate themselves in this new market. To begin with the majority of business will be targetting the container-curious and mainly talking up the benefits of containers and Kubernetes. But some potentialy customers are going to insist on comparing Kubernetes distributions and winning there is going to be about clear differentiation. Do you want to be the budget offering or the provider with the unique selling point?

Interesting questions

An observation at the moment is that all the current Kubernetes distributions I’m aware of are vendor-owned. Whether Open Source or not, they are driven by a single vendor (CoreOS, Red Hat, Apprenda, etc.) It’s interesting to see whether, in the current climate, we see a genuinely free and open source Kubernetes distribution emerge, similar to the role Debian plays in the Linux distribution world.

Unikernels and The End of the General Purpose Operating System

The previous post went into why I think the days of the general purpose operating system (for servers) are numbered. But one interesting area I didn’t comment on (but did talk about in the talk of the same name) was Unikernels.

It’s all about cost

One of the topics I didn’t really touch on in discussing the end of the generally purpose operating system was cost. Historically, maintaining a general purpose operating system has been a costly endeavour, something only the largest companies or communities could sustain by themselves. Think Red Hat, Oracle, Microsoft, Sun, IBM, Debian, etc. The result of that is the assumption when building software that you should target one or more of a small number of operating systems. In doing so you’re ceding some ground, and likely some revenue, to another vendor. You’re also stuck with any underlying limitations of that OS as well as its release cadence. And invariably you’re also stuck with the multiplying support cost of supporting your software on multiple versions of that OS over time.

I would posit that up until relatively recently the cost of that support burden was hugely outweighted by the cost of maintaining an actual operating system. But that’s now changing, as I outlined in the previous post. Now a small or medium sized software company (be it CoreOS, Rancher, Docker, Pivotal, etc.) can build and maintain it’s own operating system as well. This is very much about the rising level of abstraction - all of the above leverage the huge efforts that go into the Linux kernel and into other projects like systemd (CoreOS) or Alpine (Docker’s Moby) for instance.

Enter Unikernels

But where do Unikernels fit into this narrative? I’d argue that they represent the fulfilment of this democratization. If building and maintaining a traditional OS is only possible for the largest of companies, and building and maintaining a more special-purpose OS (say for running containers, or a storage device) is cost-effective for medium sized softare companies, then Unikernels will allow anyone to build their own single-purpose operating systems.

There are other technical reasons for (and against) Unikernels as an approach but most focus on the technical. I think the economic side is worth some consideration too. And not just the typical development and support costs, but the ability to own the end-to-end unit of software has lots of benefits, and Unikernels may make those benefits available to everyone, including small organisations and individuals.

The End of the General Purpose Operating System

As interesting chat on Twitter today reminded me that not everyone is probably aware that we’re seeing a concerted attempt to dislodge the general purpose operating system from our servers.

I gave a talk about some of this nearly two years ago and I though a blog post looking at what I got right, what I got wrong and what’s actually happening would be of interest to folks. The talk was written only a few months after I joined Puppet. With a bunch more time working for a software vendor there are some bits I missed in my original discussion.

What do you mean by general purpose and by end?

First up, a bit of clarification. By general purpose OS I’m referring to what most people use for server workloads today - be it RHEL or variants like CentOS or Fedora, or Debian and derivatives like Ubuntu. We’ll include Arch, the various BSD and opensolaris flavours and Windows too. By end I don’t literally mean they go away or stop being useful. My hypothosis is that, slowly to begin with then more quickly, they cease to be the default we reach for when launching new services.

The hypervisor of containers

The first part of the talk included a discussion of what I’d referred to as the hypervisor of containers, what today would more likely be referred to as a CaaS, or containers as a service. I even speculated that VMWare would have to ship something in this space (See vSphere Integrated Containers and the work on Photon OS) and that counting out OpenShift would be premature (OpenShift 3 shipped predominantly as a Kubernetes distribution). I’ll come back to why this is a threat to your beloved Debian servers shortly.

The race to PID1

For anyone who has run Docker you’ll likely have wrestled with the question of where does the role of the host process supervisor (probably systemd) start and the container process supervisor (the Docker engine) end? Do you have to interact directly with both of them?

Now imagine if all of the software on your servers was run in containers. Why do I need two process supervisors now with 100% overlap? The obvious answer is you don’t, which is why the fight between Docker and systemd is inevitable. Note that this isn’t specific to Docker either. In-scope for cri-o is Container process lifecycle management.

Containers as the unit of software

Hidden behind my hypothosis, which mainly went unsaid, was that containers are becoming the unit of software. By which I mean the software we build or buy will increasingly be distributed as containers and run as containers. The container will carry with it enough metadata for the runtime to determine what resources are required to run it.

The number of simplying assumption that come from this shared contract should not be underestimated. At least at the host level you’re likely to need lots of near-identical hosts, all simply advertising their capabilities to the container scheduler.

Operating system as implementation detail

What we’re witnessing in the market is the development of vertically integrated stacks.

  • Docker for Mac/Windows/AWS/Azure ships with it’s own operating system, an Alpine Linux derivative nicknamed Moby, which is not intended for direct management by end users.
  • Tectonic from CoreOS is a Kubernetes distribution which runs atop a cluster of managed CoreOS hosts. Most of the operating system is managed with frequent atomic rolling updates.
  • OpenShift Enterprise from RedHat is another Kubernetes derivative, this time running atop Atomic host.
  • Pivotal CloudFoundry ships with the IaaS, host OS, kernel, file system, container OS all tested together

In all of these cases the operating system is an implementation detail of the higher level software. It’s not intended to be directly managed, or at least managed to the same degree as the general purpose OS you’re running today.

This is how the end comes for the majority of your general purpose operating system running servers. The machines running containers will be running something more single purpose, and more and more of the software you’re running will be running in containers.

The reason why you’ll do this, rather than compose everything yourself, is compatability. Whether it’s kernel versions, file system drivers, operating system variants or a hundred variations that make your OS build different from mine. Building and testing software that runs everywhere is a sisyphean task. Their is also the commercial angle at play here, and the advantage of being able to support a single validated product to everyone.

Implications

There are lots of implications to this move, and it’s going to be interesting to see how it plays out with both early adopters and enterprise customers alike.

  • What does this mean for corporate operating system policies?
  • How do standard agent-based monitoring systems work in a world of closed vertical stacks?
  • Will we see this pattern for other types of service in the AWS Marketplace, where instance launched are inaccessible but automatically updating?
  • How does such fast moving software work in environments with rigid change control processes or audit requirements?
  • Many large organisations will end up running more than one of these types of system, how best to manage such heterogenous environments?
  • Will we see push back from some parties? In particular the open source community who may see this mainly serving the needs of vendors?
  • Does the end of the general purpose OS lead to greater specialism amongst systems administrators?

I’d love to chat about any of this with other folks who have given it some thought. It’s interesting watching grand changes play out across the industry and picking up on patterns that are likely obvious in hindsight. And if you like this sort of thing let me know and I’ll try and find time for more speculation.

InfraKit Hello World

Docker just shipped InfraKit a few days ago at LinuxCon and, while at the Docker Distributed Systems Summit, I wanted to see if I could get a hello world example up and running. The documentation is lacking at the moment, epecially around how to tie the different components like instances and flavors together.

The following example isn’t going to do anything particularly useful, but it’s hopefully simple enough to help anyone else trying to get started. I’m assuming you’ve checked out and built the binaries as described in the README.

First create a directory. We’re going to be using InfraKit to manage local files in that directory as part of the demo.

mkdir test

Now create an InfraKit configuration file. We’re going to use the file instance plugin to manage files in out directory. This means everything works on the local machine, rather than trying to launch real infrastructure in AWS or similar. InfraKit also requires a flavor plugin. I’m using vanilla here just to meet the requirement for a flavor plugin, but it’s not going to actually do anything in this demo. It might be useful to write a noop flavor plugin or similar.

cat garethr.json
{
    "ID": "garethr",
    "Properties": {
        "Instance" : {
            "Plugin": "instance-file",
            "Properties": {
            }
        },
        "Flavor" : {
            "Plugin": "flavor-vanilla",
            "Properties": {
                "Size": 1
            }
        }
    }
}

InfraKit is based on running separate plugins. Each plugin runs as a separate process and provides a filesystem socket in /run/infrakit/plugins. First start up the file plugin:

$ ./infrakit/file --dir=./test
INFO[0000] Starting plugin
INFO[0000] Listening on: unix:///run/infrakit/plugins/instance-file.sock
INFO[0000] listener protocol= unix addr= /run/infrakit/plugins/instance-file.sock err= <nil>

Next, in a separate terminal run the vanilla plugin:

$ ./infrakit/vanilla
INFO[0000] Starting plugin
INFO[0000] Listening on: unix:///run/infrakit/plugins/flavor-vanilla.sock
INFO[0000] listener protocol= unix addr= /run/infrakit/plugins/flavor-vanilla.sock err= <nil>

An finally run the group plugin. I’m passing --log=5 to enable more verbose outout so it’s easier to see what’s going on with the group.

$ ./infrakit/group --log=5
INFO[0000] Starting discovery
DEBU[0000] Opening: /run/infrakit/plugins
DEBU[0000] Discovered plugin at unix:///run/infrakit/plugins/instance-file.sock
INFO[0000] Starting plugin
INFO[0000] Starting
INFO[0000] Listening on: unix:///run/infrakit/plugins/group.sock
INFO[0000] listener protocol= unix addr= /run/infrakit/plugins/group.sock err= <nil>

With that all setup we can create a group based on our configuration file from above.

$ ./infrakit/cli group --name group watch garethr.json
watching garethr

Have a look in the test directory. You should see a single file has been created.

$ ls test
instance-1475833380

Let’s delete that file and see what happens:

rm test/*

Hopefully InfraKit will spot the instance (a file in this case) no longer exists and recreate it. You should see something like the following in the logs:

INFO[0612] Created instance instance-1475833820 with tags map[infrakit.config_sha:B2MsacXz8V_ztsjAzu3tu3zivlw= infrakit.group:garethr]

This is obviously a less-than-useful example but hopefully provides a good hello world example for anyone trying to run InfraKit in it’s current early stage.

Everyone is Not a Software Company

The Everyone is a Software Company meme has been around for a number of years, but it feels increasingly hard to get away from recently. That prompted this post.

But what do we mean by Software Company?

To be software company you’re going to need to employee software engineers and other professionals. Applying that logic to a large number of companies at once, and looking at how existing software companies are setup, we find a few large problems.

Google as an example

In my talk at Velocity, entitled The Two Sides of Google Infrastructure for Everyone Else I argued both for and against the idea of wholesale adoption of Google-like software and development/operations practices. Even though they derive the lions share of revenue from advertising it’s easy to argue that Google are a software company. But what does that look like? What makes Google a software company?

From the Google Annual Report 2015

61,814 full-time employees: 23,336 in research and development, 19,082 in sales and marketing, 10,944 in operations, and 8,452 in general and administrative functions

So, roughly 50% of Google is involved in building or running software. Glassdoor says salaries for engineers at Google average about $126,000-$162,000.

The US Bureau of Labor Statistics says that in 2014 the number of computer programming jobs in the US was 1,114,000, with median pay in 2015 of $100,690 a year. The total number of jobs in the US is about 143 million, with the average wages at $44,569.20 according to the Social Security Administration.

The Google Annual Report also states:

Competition for qualified personnel in our industry is intense, particularly for software engineers, computer scientists, and other technical staff

So, quick summary:

  • Software engineers are expensive relative to others employees
  • Demand for the best engineers means even higher wages
  • Proportionally there aren’t many software developers
  • There isn’t a large surplus of unemployed software engineers

Now the data above is mainly from US sources, although the Google data is from an international company with offices around the world. My experience says this is likely similar in Europe. Looking into data for India and China would be super interesting I’d wager.

Problems

One obvious problem is short-term supply and demand. Everyone wants experienced software folks for their transformation effort. But the more organisations that buy into the everyone is a software company story the greater the demand for a finite supply of people. For most that means you’ll to able to find less people that you want because of competition and afford even less people because all that competition pushes up salaries.

I’ve seen that firsthand while working for the UK Government. People occasionally complained that Government was hampering commercial organisations growth by employing lots of developers and operations people in London.

You’re also immediately in competition for software professionals with existing software companies. Given the high salaries, most of those employers already have developer friendly working environments and established hiring practices suited to luring developers to work for them. This sort of special case is hard for large companies without an existing empowered developer organisation. I saw a lot of that at the Government as well.

But the real macro problems are much more interesting. Even if you think 50% is a high mark for the ratio of software folk to others, you probably agree you need a lot more than you have today. And those developers just don’t exist today to allow everyone to be a software company. Nor would I argue is education in the near term producing enough skilled people to fill that gap tomorrow. So, what happens?

  • Does everyone sort-of become a software company but not quite?
  • Do most organisations struggle to hire and maintain a software team and see the endeavour fail?
  • Do increasing numbers of developers end up working for a small number of larger and larger software companies?
  • Does outsourcing bounceback, adapt and demonstrate innovation and transformation qualities to go along with the scale?
  • Countries like India or China are able to produce enough software engineers at scale to allow there companies to act on everyone becoming a software company?
  • We see clear winners and losers, ie. companies which become software companies and accelarate away from those that don’t?

Personally I think to take advantage of the idea behind the meme we’re going to need order of magnitude more efficient approaches to software delivery. What that looks like is the most interesting question of all.

Caveats

The above is not a detailed analysis, and undoutedly has a few holes. It also doesn’t overly question the advantage of being a software company, or really question what we actually mean by everyone. But I think the central point holds: Everyone is NOT a software company, nor will everyone be a software company any time soon, unless we come up with a fundamentally better approach to service delivery.