high_scalability high_scalability-2014 high_scalability-2014-1628 knowledge-graph by maker-knowledge-mining
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Introduction: This is a guest post by Benjamin Wootton , CTO of Contino , a London based consultancy specialising in applying DevOps and Continuous Delivery to software delivery projects. Microservices are a style of software architecture that involves delivering systems as a set of very small, granular, independent collaborating services. Though they aren't a particularly new idea, Microservices seem to have exploded in popularity this year, with articles, conference tracks, and Twitter streams waxing lyrical about the benefits of building software systems in this style. This popularity is partly off the back of trends such as Cloud, DevOps and Continuous Delivery coming together as enablers for this kind of approach, and partly off the back of great work at companies such as Netflix who have very visibly applied the pattern to great effect. Let me say up front that I am a fan of the approach. Microservices architectures have lots of very real and significant benefits: The service
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1 Microservices are a style of software architecture that involves delivering systems as a set of very small, granular, independent collaborating services. [sent-2, score-0.318]
2 I am currently involved in architecting a system based around Microservices, and whilst the individual services are very simple, a lot of complexity exists at a higher level level in terms of managing these services and orchestrating business processes throughout them. [sent-8, score-0.531]
3 Where a monolithic application might have been deployed to a small application server cluster, you now have tens of separate services to build, test, deploy and run, potentially in polyglot languages and environments. [sent-12, score-0.754]
4 All of these services potentially need clustering for failover and resilience, turning your single monolithic system into, say, 20 services consisting of 40-60 processes after we've added resilience. [sent-13, score-0.689]
5 Throw in load balancers and messaging layers for plumbing between the services and the estate starts to become pretty large when compared to that single monolithic application that delivered the equivalent business functionality! [sent-14, score-0.568]
6 Sure, we can avoid some of these changes with backwards compatibility approaches, but you often find that a business driven requirements prohibit staged releases anyway. [sent-33, score-0.297]
7 Releasing a new product line or an externally mandated regulatory change for instance can force our hand to release lots of services together. [sent-34, score-0.279]
8 This represents additional release risk over the alternative monolithic application due to the integration points. [sent-35, score-0.408]
9 If we let collaborating services move ahead and become out of sync, perhaps in a canary releasing style, the effects of changing message formats can become very hard to visualise. [sent-36, score-0.53]
10 That does however introduce more potentially synchronous coupling into the system, so is not a decision we would take lightly. [sent-41, score-0.269]
11 We could duplicate the effort, adding the tax calculation into all of the services that need it. [sent-42, score-0.25]
12 This can be useful, but it won't always work in a polyglot environment and introduces coupling which may mean that services have to be released in parallel to maintain the implicit interface between them. [sent-45, score-0.347]
13 It seems to me that all three of these options are sub-optimal as opposed to writing the piece of code once and making it available throughout the monolithic application. [sent-47, score-0.281]
14 Backwards compatibility and graceful degradation are nice properties to have that we might not have implemented within the monolithic alternative, helping keep the system up and more highly available than the monolithic application would be. [sent-55, score-0.704]
15 Distributed systems are an order of magnitude more difficult to develop and test against, so again the bar is raised vs building that unsexy monolithic application. [sent-57, score-0.468]
16 Related to the abovei point, systems built in the Microservices style are likely to be much more asynchronous than monolithic applications, leaning on messaging and parallelism to deliver their functionality. [sent-59, score-0.584]
17 Testability Challenges With so many services all evolving at different paces and different services rolling out canary releases internally, it can be difficult to recreate environments in a consistent way for either manual or automated testing. [sent-62, score-0.582]
18 When we add in asynchronicity and dynamic message loads, it becomes much harder to test systems built in this style and gain confidence in the set of services that we are about to release into production. [sent-63, score-0.773]
19 We can test the individual service, but in this dynamic environment, very subtle behaviours can emerge from the interactions of the services which are hard to visualise and speculate on, let alone comprehensively test for. [sent-64, score-0.305]
20 I am a big believer in this approach - lowing the barriers to release and leaning continuous delivery in order to speed up lean delivery. [sent-66, score-0.413]
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