Skip to main content

Release It - Highlights Part 1

Release It! is one of the most useful books I've read. The advice and suggestions inside certainly change your perspective on how to write software. My key takeaway is that software should be cynical. Expect the worst, expect failures and put up boundaries. In the majority of cases these failures will be trigged by integration points with other systems, be it third parties or your own.

My rough notes and snippets will be spread across the following two posts. There is much more to the book than this, including various examples of real life systems failing and how they should have handled the problem in the first place.

Shared Resources

  • Shared Resources can jeopardize scalability.
  • When a shared resource gets overloaded, it will become a bottleneck.
  • If you provide the front end system, test what happens if the back end is slow/down. If you provide the back end, test what happens if the front end is under heavy load.


  • Generating a slow response is worse than refusing to connect or timing out.
  • Slow responses trigger cascading failures.
  • Slow responses on the front end trigger more requests. Such as the user hitting refresh a few times, therefore generating more load ironically.
  • You should error when a response exceeds the systems allowed time, rather than waiting.
  • Most default timeouts of libraries and frameworks are far too generous - always configure manually.
  • One of the worst places that scaling effects will bite you is with point to point communication. Favour other alternatives such as messaging to remove this problem.


  • When calling third parties, services levels only decrease.
  • Make sure even without a third party response your system can degrade gracefully.
  • Be careful when crafting SLA's. Do not simply state 99.999%, it costs too much to hit this target and most systems don't need this sort of uptime.
  • Reorient the discussion around SLA's to focus on features, not systems.
  • You cannot offer a better SLA than the worst of any external dependencies you use.


  • Your application probably trusts the database far too much.
  • Design with scepticism and you will achieve resilience.
  • What happens if the DB returns 5 million rows instead of 5 hundred? You could run out of memory trying to load all this. The only answers a query can return is 0, 1 or many. Don't rely on the database to follow this limit. Other systems or batch processes may not respect this rule and insert too much data.
  • After a system is in production, fetch results can return huge result sets. Unlike developer testing where only a small subset of data is around.
  • Limit your DB queries, e.g. SELECT * FROM table LIMIT 15 (the wildcard criteria would be substituted)
  • Put limits into other application protocols such REST endpoints via paging or offsets.

Circuit Breakers

  • Now and forever networks will always be unreliable.
  • The timeout pattern prevents calls to integration points from becoming blocked threads.
  • Circuit Breakers area way of automatically degrading functionality when a system is under stress.
  • Changes in a circuit breaker should always be logged and monitored.
  • The frequency of state changes in a circuit breaker can help diagnose other problems with the system.
  • When there is a problem with an integration point, stop calling it during a cool off period. The circuit breaker will enable this.
  • Popping a circuit breaker always indicates a serious problem - log it.


Popular posts from this blog

Constant Object Anti Pattern

Most constants are used to remove magic numbers or variables that lack context. A classic example would be code littered with the number 7. What does this refer to exactly? If this was replaced with DaysInWeek or similar, much clarity is provided. You can determine that code performing offsets would be adding days, rather than a mysterious number seven.Sadly a common pattern which uses constants is the use of a single constant file or object. The beauty of constants is clarity, and the obvious fact such variables are fixed. When a constant container is used, constants are simply lumped together. These can grow in size and often become a dumping ground for all values within the application.A disadvantage of this pattern is the actual value is hidden. While a friendly variable name is great, there will come a time where you will want to know the actual value. This forces you to navigate, if only to peek at the value within the constant object. A solution is to simple perform a refactor …

Three Steps to Code Quality via TDD

Common complaints and problems that I've both encountered and hear other developers raise when it comes to the practice of Test Driven Development are: Impossible to refactor without all the tests breakingMinor changes require hours of changes to test codeTest setup is huge, slow to write and difficult to understandThe use of test doubles (mocks, stubs and fakes is confusing)Over the next three posts I will demonstrate three easy steps that can resolve the problems above. In turn this will allow developers to gain one of the benefits that TDD promises - the ability to refactor your code mercifully in order to improve code quality.StepsStop Making Everything PublicLimit the Amount of Dependencies you Use A Unit is Not Always a Method or ClassCode quality is a tricky subject and highly subjective, however if you follow the three guidelines above you should have the ability to radically change implementation details and therefore improve code quality when needed.

DRY vs DAMP in Tests

In the previous post I mentioned that duplication in tests is not always bad. Sometimes duplication becomes a problem. Tests can become large or virtually identically excluding a few lines. Changes to these tests can take a while and increase the maintenance overhead. At this point, DRY violations need to be resolved.SolutionsTest HelpersA common solution is to extract common functionality into setup methods or other helper utilities. While this will remove and reduce duplication this can make tests a bit harder to read as the test is now split amongst unrelated components. There is a limit to how useful such extractions can help as each test may need to do something slightly differently.DAMP - Descriptive and Meaningful PhrasesDescriptive and Meaningful Phrases is the alter ego of DRY. DAMP tests often use the builder pattern to construct the System Under Test. This allows calls to be chained in a fluent API style, similar to the Page Object Pattern. Internally the implementation wil…