Introducing Microservices iQ

August 01 2016

As part of AppDynamics Summer ‘16 release, we are announcing Microservices iQ, a new intelligent application performance engine, that enables enterprises to efficiently manage microservice based application environments and deliver performance that delights their customers while exceeding their scale, sophistication and velocity expectations.

Microservice architecture is an increasingly popular style of enterprise application development where instead of large monolithic code bases, applications are comprised of many fine-grained components or services developed and operated by smaller teams. These independent services may be used in conjunction with other services to support one or more business transactions.


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Figure 1: Monolith vs. Microservices 

A microservices architecture significantly enhances the agility and accelerates the velocity of continuous integration and delivery of enterprise applications. However, this approach can result in an exponentially larger number of microservices that are loosely coupled and communicate primarily via asynchronous mechanism, creating increased complexity and a significant management challenge.

AppDynamics, now powered by Microservices iQ, automatically detects the service endpoints of the microservices architecture and allow them to be viewed in isolation of distributed business transactions. We can understand microservice lifecycles and ensure data continuity despite the intermittent presence of the underlying application infrastructure. We can check the availability of microservices within your network as well as the availability of 3rd-party services. Our new Contention Analysis provides the next level of performance diagnostics for microservices, ensuring that a particular service is not a bottleneck in blocking business transactions.

Here are the key capabilities of the AppDynamics Microservices iQ:

Service Endpoints: AppDynamics automatically detects service endpoints of your microservice architecture, enabling you to shine a spotlight on microservices without worrying about the entire distributed business transaction that uses it.

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Figure 2: Service Endpoint Dashboard

DevOps teams can monitor the key performance indicators (KPIs) like calls per minute, average response and errors per minute of their microservices not only in production, but also in early development and throughout the entire lifecycle using the Service Endpoint Dashboard (Figure 2).

The dashboard also lists the snapshots with detailed diagnostics that enables the DevOps teams to drill down and isolate the root cause any performance issues affecting the microservices.  

Thread Contention Analysis: Given the independent nature of components in microservice architectures, it is more likely that a particular microservice is invoked as part of multiple business transactions and can become a performance bottleneck for those transactions if it blocks their execution. The new thread contention analyzer helps identify methods, within the scope of service endpoints, where threads are blocked by identifying block time, blocking object and the blocking line of code.  As you can see in the screenshot (Figure 3) of the new thread contention analysis window for the service endpoint, blocking threads, blocking object, block time and the reference to the line of the code are highlighted.

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Figure 3: Thread Contention Analysis

This feature can significantly minimize the time required to isolate and resolve application performance issues with the microservices and the business transactions invoking them.

Elasticity Management: In highly dynamic environments, with microservices deployed in elastic infrastructure like containers or the cloud, the underlying infrastructure nodes may scale up or down rapidly, creating a management nightmare to track these microservices and the infrastructure nodes in the context of the associated business transaction.

AppDynamics maintains logical identity and historical data about these transient nodes for a certain period making it easy to track them in context of a business transaction. In addition, it minimizes the system’s overhead by recycling the logical node identity after a certain period to ensure that the enterprise applications can scale to meet their growing business needs.

Extending AppDynamics App iQ Platform: Microservices iQ extends AppDynamics’ existing App iQ Platform that enables enterprises to deliver performance that exceeds the scale, sophistication, and velocity expectations of today’s customers. The platform is the foundation to AppDynamics’ customers’ success and powered by intelligent Application Performance Engines. These intelligent performance engines work in concert to help ensure enterprises can deliver peak performance across any application, user engagement and business transaction.

The new Microservices iQ capabilities enhance the core Appdynamics Platform that is already designed to provide end-to-end visibility into agile application infrastructure where microservices are deployed. For example, AppDynamics can automatically discover a large number of microservices, dynamically baselines their performance, collects deep diagnostics and alerts when the performance deviates from the normal baseline. Manually instrumenting these large number of microservices and setting static threshold for altering can be a very difficult task if not impossible.   

To learn more about AppDynamics Microservices iQ, refer

Anand Akela
Anand Akela is Director of Product Marketing for Application Performance Management (APM) at AppDynamics. Prior to his current role, Anand was head of product marketing of APM at CA Technologies. Earlier he worked at Oracle and HP in various product marketing, product management, and engineering roles in the systems management, servers, data center energy efficiency, and enterprise software areas. Anand has more than 20 years of experience in product marketing, product management, strategic planning and software development. Anand received his MBA from The Fuqua School of Business, Duke University and a B.S. in Computer Science from Pune University in India. You can follow Anand on twitter at

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