Transforming your monolithic application into a microservices-based one is not as easy as many think. When you are breaking a software down into smaller pieces, you're moving the communication to the network layer and the complexity of your architecture is heavily increasing. Other issues arise as well since performance monitoring and finding the root source of an error becomes extremely challenging.
With the rise of microservices, developers need proper Application Performance Management (APM) tools to develop and operate their applications successfully. This blog examines the particular difficulties of monitoring microservices and what APM should be able to do to alleviate the major pain-points of monitoring and debugging them.
Figuring Out What Breaks in a Microservices Application
In a monolithic application, specific code pieces are communicating in the applications memory. It means that when something breaks, the log files will probably be useful to find the cause of an error and you can start debugging right away.
When something goes wrong in a microservices call-chain – called distributed transactions – all of the services participating in that request will throw back an error. It means that you need an excellent logging system, and if you have one, you'll still experience problems since you have to manually correlate the log files to find out what caused the trouble in the first place.
What's the solution to this problem? Distributed Tracing.
For microservices applications, there is a much more sophisticated application performance monitoring method available, called Distributed Tracing.
For distributed tracing, you have to attach a correlation ID to your requests which you can use to track what services are communicating with each other. With these IDs, you can to reverse engineer what happened during an error since all of the services involved in a request will be there for you to see instantly.
Next-gen APM solutions can already attach correlation IDs to requests and can also group the services taking part in a transaction and visualize the exact dataflow on a simple tree-graph. A tool like this enables you to see the distributed call stacks, the root cause of an error, and the dependencies between your microservices.
A distributed tracing timeline shows all of the services taking part in a certain transaction and the source of the error that later propagated back to all of them
There are only a few Distributed Tracing solutions available right now, but you can find open source solutions for Java monitoring and a SaaS solution focusing on Node.js – the technology primarily used for building microservices.
The concept of Distributed Tracing is based on Google’s Dapper whitepaper, which is publicly available here.
Increasing Architecture Complexity and Slow Response Times
As I mentioned above, increasing architecture complexity comes by the definition with microservices.
In a microservices application, the services will usually use a transport layer, like the HTTP protocol, RabbitMQ or Kafka. It will add delays to the internal communication of your application, and when you put services into a call chain, your response times will be higher. A modern APM solution must be prepared for this, and support message queue communication to map out a distributed system. If you have one, you'll be able to figure out what makes it slow.
Companies that build microservices should be able to deal with slow response times by using a distributed tracing APM tool. Correlation IDs let you visualize whole call chains and look for slow response times, whether it's caused by a slow service or the slow network.
If the transaction timeline graph shows that your services are fine, but your network is slow, you can to speed up your application by investigating that. One time, we could figure out that our PaaS provider was using external routing, so every request between our services went outside the public network and back, it reached more than 30 network hops, which caused the bad response time. The next step, in this case, was to choose another without external routing.
Application performance monitoring solutions have been around for a while, offering the same functionalities for years without major breakthroughs. This has to change. The way how we develop and deploy software is not the same than it was three years ago, and legacy APM tools are not helping as much as they used to. We need solutions that are treating microservices as first class citizens, and the developers who are building them too.
Gergely Nemeth is Co-Founder and CEO of RisingStack.
You've heard of DevOps and SecOps, but NetOps? NetOps is a natural progression of legacy Network Operations to foster more efficient and resilient infrastructures through automation and intelligence. The efficacy of NetOps personnel is reliant upon understanding five key elements of a NetOps Platform and how to best utilize and implement each ...
It's also important to keep the diversity of the Advanced IT Analytics (AIA) landscape in mind as you plan for your investments. AIA is still not a market in the traditional sense. My vision of AIA is rather an arena of fast-growing exploration and invention, in which in-house development is beginning to cede to third-party solutions that can accelerate time to value ...
Most application performance monitoring (APM) tools offer user experience monitoring and transaction tracing capabilities. But, when there is infrastructure slowness affecting the application, these APM tools cannot always pinpoint the root cause of problems. This is where unified infrastructure monitoring comes in ...
Business transaction monitoring is the approach commonly used to identify and diagnose server-side processing slowness for web applications. While it is an important component of an application performance monitoring strategy, a key question is whether business transaction tracing is sufficient for ensuring peak application performance ...
Gartner highlighted the top strategic technology trends that will impact most organizations in 2018. The next trends focus on blending the digital and physical worlds to create an immersive, digitally enhanced environment. The last three refer to exploiting connections between an expanding set of people and businesses, as well as devices, content and services to deliver digital business outcomes ...
Gartner highlighted the top strategic technology trends that will impact most organizations in 2018. The first three strategic technology trends explore how artificial intelligence (AI) and machine learning are seeping into virtually everything and represent a major battleground for technology providers over the next five years ...
In the Riverbed Future of Networking Global Survey, more than half of the respondents acknowledged that achieving operational agility is critical to the success of a modern enterprise, and next-generation networks as well as the technology to support them are key to reaching this goal ...
Legacy infrastructures are holding back their cloud and digital strategies, according to the Riverbed Future of Networking Global Survey 2017. Nearly all survey respondents agree that legacy network infrastructure will have difficulty keeping pace with the changing demands of the cloud and hybrid networks ...