Welcome!

Related Topics: Java IoT, Industrial IoT, Microservices Expo, Machine Learning , Apache, @DXWorldExpo

Java IoT: Article

Fix Memory Leaks in Java Production Applications

A memory diagnostics approach for production identifies and fixes the root cause of the problem

Adding more memory to your JVMs (Java Virtual Machines) might be a temporary solution to fixing memory leaks in Java applications, but it for sure won't fix the root cause of the issue. Instead of crashing once per day it may just crash every other day. "Preventive" restarts are also just another desperate measure to minimize downtime, but, let's be frank: this is not how production issues should be solved.

One of our customers - a large online retail store - ran into such an issue. They run one of their online gift card self-service interfaces on two JVMs. During peak holiday seasons when users are activating their gift cards or checking the balance, crashes due to OOM (Out Of Memory) were more frequent, which caused bad user experience. The first "measure" they took was to double the JVM Heap Size. This didn't solve the problem as JVMs were still crashing, so they followed the memory diagnostics approach for production as explained in Java Memory Leaks to identify and fix the root cause of the problem.

Before we walk through the individual steps, let's look at the memory graph that shows the problems they had in December during the peak of the holiday season. The problem persisted even after increasing the memory. They could fix the problem after identifying the real root cause and applying specific configuration changes to a third-party software component.

After identifying the actual root cause and applying necessary configuration changes did the memory leak issue go away? Increasing Memory was not even a temporary solution that worked.

Step 1: Identify a Java Memory Leak
The first step is to monitor the JVM/CLR Memory Metrics such as Heap Space. This will tell us whether there is a potential memory leak. In this case we see memory usage constantly growing, resulting in an eventual runtime crash when the memory limit is reached.

Java Heap Size of both JVMs showed significant growth starting Dec 2nd and Dec 4th resulting in a crash on Dec 6th for both JVMs when the 512MB Max Heap Size was exceeded.

Step 2: Identify problematic Java Objects
The out-of-memory exception automatically triggers a full memory dump that allows for an analysis of which objects consumed the heap and are most likely to be the root cause of the out-of-memory crash. Looking at the objects that consumed most of the heap below indicates that they are related to a third-party logging API used by the application.

Sorting by GC (Garbage Collection) Size and focusing on custom classes (instead of system classes) shows that 80% of the heap is consumed by classes of a third-party logging framework

A closer look at an instance of the VPReportEntry4 shows that it contains five strings - with one consuming 23KB (as compared to several bytes of other string objects).This also explains the high GC Size of the String class in the overall Heap Dump.

Individual very large String objects as part of the ReportEntry object

Following the referrer chain further up reveals the complete picture. The EventQueue keeps LogEvents in an Array, which keeps VPReportEntrys in an Array. All of these objects seem to be kept in memory as the objects are being added to these arrays but never removed and therefore not garbage collected:

Following the referrer tree reveals that global EventQueue objects hold on to the LogEvent and VPReportEntry objects in array lists which are never removed from these arrays

Step 3: Who allocates these objects?
Analyzing object allocation allows us to figure out which part of the code is creating these objects and adding them to the queue. Creating what is called a "Selective Memory Dump" when the application reached 75% Heap Utilization showed the customer that the ReportWriter.report method allocated these entries and that they have been "living" on the heap for quite a while.

It is the report method that allocates the VPReportEntry objects that stay on the heap for quite a while

Step 4: Why are these objects not removed from the Heap?
The premise of the third-party logging framework is that log entries will be created by the application and written in batches at certain times by sending these log entries to a remote logging service using JMS. The memory behavior indicates that even though these log entries might be sent to the service, these objects are not always removed from the EventQueue leading to the out-of-memory exception.

Further analysis revealed that the background batch writer thread calls a logBatch method, which loops through the event queue (calling EventQueue.next) to send current log events in the queue. The question is whether as many messages were taken out of the queue (using next) vs put into the queue (using add) and whether the batch job is really called frequently enough to keep up with the incoming event entries. The following chart shows the method executions of add, as well as the call to logBatch highlighting that logBatch is actually not called frequently enough and therefore not calling next to remove messages from the queue:

The highlighted area shows that messages are put into the queue but not taken out because the background batch job is not executed. Once this leads to an OOM and the system restarts it goes back to normal operation but older log messages will be lost.

Step 5: Fixing the Java Memory Leak problem
After providing this information to the third-party provider and discussing with them the number of log entries and their system environment the conclusion was that our customer used a special logging mode that was not supposed to be used in high-load production environments. It's like running with DEBUG log level in a high load or production environment. This overwhelmed the remote logging service and this is why the batch logging thread was stopped and log events remained in the EventQueue until the out of memory occurred.

After making the recommended changes the system could again run with the previous heap memory size without experiencing any out-of-memory exceptions.

The Memory Leak issue has been solved and the application now runs even with the initial 512MB Heap Space without any problem.

They still use the same dashboards they have built to troubleshoot this issue, and to monitor for any future excessive logging problems.

These dashboards allow them to verify that the logging framework can keep up with log messages after they applied the changes.

Conclusion
Adding additional memory to crashing JVMs is most often not a temporary fix. If you have a real Java memory leak it will just take longer until the Java runtime crashes. It will even incur more overhead due to garbage collection when using larger heaps. The real answer to this is to use the simple approach explained here. Look at the memory metrics to identify whether you have a leak or not. Then identify which objects are causing the issue and why they are not collected by the GC. Working with engineers or third-party providers (as in this case) will help you find a permanent solution that allows you to run the system without impacting end users and without additional resource requirements.

Next Steps
If you want to learn more about Java Memory Management or general Application Performance Best Practices check out our free online Java Enterprise Performance Book. Existing customers of our APM Solution may also want to check out additional best practices on our APM Community.

More Stories By Andreas Grabner

Andreas Grabner has been helping companies improve their application performance for 15+ years. He is a regular contributor within Web Performance and DevOps communities and a prolific speaker at user groups and conferences around the world. Reach him at @grabnerandi

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


Latest Stories
Sometimes I write a blog just to formulate and organize a point of view, and I think it’s time that I pull together the bounty of excellent information about Machine Learning. This is a topic with which business leaders must become comfortable, especially tomorrow’s business leaders (tip for my next semester University of San Francisco business students!). Machine learning is a key capability that will help organizations drive optimization and monetization opportunities, and there have been some...
"Storpool does only block-level storage so we do one thing extremely well. The growth in data is what drives the move to software-defined technologies in general and software-defined storage," explained Boyan Ivanov, CEO and co-founder at StorPool, in this SYS-CON.tv interview at 16th Cloud Expo, held June 9-11, 2015, at the Javits Center in New York City.
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, whic...
The question before companies today is not whether to become intelligent, it’s a question of how and how fast. The key is to adopt and deploy an intelligent application strategy while simultaneously preparing to scale that intelligence. In her session at 21st Cloud Expo, Sangeeta Chakraborty, Chief Customer Officer at Ayasdi, provided a tactical framework to become a truly intelligent enterprise, including how to identify the right applications for AI, how to build a Center of Excellence to oper...
While some developers care passionately about how data centers and clouds are architected, for most, it is only the end result that matters. To the majority of companies, technology exists to solve a business problem, and only delivers value when it is solving that problem. 2017 brings the mainstream adoption of containers for production workloads. In his session at 21st Cloud Expo, Ben McCormack, VP of Operations at Evernote, discussed how data centers of the future will be managed, how the p...
ChatOps is an emerging topic that has led to the wide availability of integrations between group chat and various other tools/platforms. Currently, HipChat is an extremely powerful collaboration platform due to the various ChatOps integrations that are available. However, DevOps automation can involve orchestration and complex workflows. In his session at @DevOpsSummit at 20th Cloud Expo, Himanshu Chhetri, CTO at Addteq, will cover practical examples and use cases such as self-provisioning infra...
As DevOps methodologies expand their reach across the enterprise, organizations face the daunting challenge of adapting related cloud strategies to ensure optimal alignment, from managing complexity to ensuring proper governance. How can culture, automation, legacy apps and even budget be reexamined to enable this ongoing shift within the modern software factory? In her Day 2 Keynote at @DevOpsSummit at 21st Cloud Expo, Aruna Ravichandran, VP, DevOps Solutions Marketing, CA Technologies, was jo...
As Marc Andreessen says software is eating the world. Everything is rapidly moving toward being software-defined – from our phones and cars through our washing machines to the datacenter. However, there are larger challenges when implementing software defined on a larger scale - when building software defined infrastructure. In his session at 16th Cloud Expo, Boyan Ivanov, CEO of StorPool, provided some practical insights on what, how and why when implementing "software-defined" in the datacent...
Blockchain. A day doesn’t seem to go by without seeing articles and discussions about the technology. According to PwC executive Seamus Cushley, approximately $1.4B has been invested in blockchain just last year. In Gartner’s recent hype cycle for emerging technologies, blockchain is approaching the peak. It is considered by Gartner as one of the ‘Key platform-enabling technologies to track.’ While there is a lot of ‘hype vs reality’ discussions going on, there is no arguing that blockchain is b...
Blockchain is a shared, secure record of exchange that establishes trust, accountability and transparency across business networks. Supported by the Linux Foundation's open source, open-standards based Hyperledger Project, Blockchain has the potential to improve regulatory compliance, reduce cost as well as advance trade. Are you curious about how Blockchain is built for business? In her session at 21st Cloud Expo, René Bostic, Technical VP of the IBM Cloud Unit in North America, discussed the b...
You know you need the cloud, but you’re hesitant to simply dump everything at Amazon since you know that not all workloads are suitable for cloud. You know that you want the kind of ease of use and scalability that you get with public cloud, but your applications are architected in a way that makes the public cloud a non-starter. You’re looking at private cloud solutions based on hyperconverged infrastructure, but you’re concerned with the limits inherent in those technologies.
Is advanced scheduling in Kubernetes achievable?Yes, however, how do you properly accommodate every real-life scenario that a Kubernetes user might encounter? How do you leverage advanced scheduling techniques to shape and describe each scenario in easy-to-use rules and configurations? In his session at @DevOpsSummit at 21st Cloud Expo, Oleg Chunikhin, CTO at Kublr, answered these questions and demonstrated techniques for implementing advanced scheduling. For example, using spot instances and co...
The use of containers by developers -- and now increasingly IT operators -- has grown from infatuation to deep and abiding love. But as with any long-term affair, the honeymoon soon leads to needing to live well together ... and maybe even getting some relationship help along the way. And so it goes with container orchestration and automation solutions, which are rapidly emerging as the means to maintain the bliss between rapid container adoption and broad container use among multiple cloud host...
The cloud era has reached the stage where it is no longer a question of whether a company should migrate, but when. Enterprises have embraced the outsourcing of where their various applications are stored and who manages them, saving significant investment along the way. Plus, the cloud has become a defining competitive edge. Companies that fail to successfully adapt risk failure. The media, of course, continues to extol the virtues of the cloud, including how easy it is to get there. Migrating...
Imagine if you will, a retail floor so densely packed with sensors that they can pick up the movements of insects scurrying across a store aisle. Or a component of a piece of factory equipment so well-instrumented that its digital twin provides resolution down to the micrometer.