Development team is taking care of effective utilization of memory for the application like efficient data structures, proper deployment of cache, handling library references, etc., In the process of coding the application, dev team is the primary creator of inefficient or indefinite loops, non-thread safe reference and poor caching. The operation team is the one who is perceiving the real time behavior of application’s memory, thereby analyzing sudden memory growth, high GC activity, and slower response time.
So, performance issues of an application have a great impact on customer satisfaction, SLAs and ROI. Thus, memory analysis is a cross functional discipline, where managers, Dev and Ops work collaboratively and collectively with a common goal of improving system performance. The manager plays a key role in setting goals of an application and driving the dev team to write the application code which is kept running by Ops team.
The Dev-Ops Memory Visibility Gap
Even though modern DevOps practices aim to coalesce development and operations, still memory analysis is a blind spot. Despite working on same application, perception of memory behavior by Dev and Ops team are discrete.
Developers appreciate ‘How memory is intended to be used ? (deployment of data structures, caching logic and object lifecycle). Meanwhile Operations team observe ‘How memory is actually used ? As neither of the team has a full snapshot of memory, it creates a visibility gap.
Main Issues created by this gap
- Misaligned Understanding of Memory Issues
- Manual Log & Dump Analysis Causes Delays
- Lack of Clear Ownership
- Blame Game During Production Incidents
- Performance ROI Drop
Why Managers must care about Memory Analysis
Application Performance Monitoring (APM) tools are employed to monitor, track and analyze the performance of applications in real time. It helps the devops team to comprehend the code where bottlenecks occur, because of slower response time and errors experienced by the errors. The metrics used for monitoring the application are CPU utilization time, memory usage, error rate, throughput and response time.
While APM tools focus on ‘What’ factor, yCrash tool focus on ‘Why’ factor. It helps to identify why it happened – root cause analysis of memory delay, slower response time. yCrash act as a Root Cause Analysis (RCA) – automated diagnostic tool. With the help of automated diagnostic tools like yCrash, there is feasibility of early detection of cause of memory leakage, correlate logs, thread dumps, heap dumps and GC behavior automatically.
Memory analysis tools as a bridge: Connecting Dev-Ops
In traditional coding, Development engineers write the code and Operation teams keep it running. Memory is the common platform where devs team write the application code and ops team analyses the execution of the same application. Improper memory analysis will lead to miscommunication among the devs and ops team, and there will not be a clear ownership among them if there are issues.
Fig: One Tool, One Table: yCrash Aligns Dev and Ops for Smarter Troubleshooting
yCrash is an integrated tool offering a bundle of diagnostic services to analyze logs, thread dumps, heap dumps.
1. GC Log Analysis
Garbage Collection (GC) logs are crucial to determine how a Java application utilizes memory, manages objects and executes. GC logs are used to observe performance bottlenecks by detecting memory leaks, identifying inefficient object creation and thrashing frequency. GCeasy is an automated Garbage Collection log analysis tool employed to analyze the performance of Java applications. It converts the raw GC logs into easy understandable insights which aids the devs and ops team to enhance the performance ROI.
2. Thread Dump Analysis
Thread dumps provide details of all threads running in a JVM at an instant of time. It elaborates each thread’s states, state traces, monitors and locks. Efficient analysis of thread dumps is essential to identify the deadlocks, threads in starvation, thread contention and CPU usage of threads, which helps to determine the cause of slower response time of the application. yCrash’ s fastThread tool automatically converts raw thread dumps into clear actionable insights.
3. Heap dump analysis
Heap dump provides a snapshot of memory of a Java application at an instant of time. It highlights all objects in the JVM heap with their classes, size, relationship among them. Automated tool of yCrash, HeapHero provide detailed insights about memory leaks, OutOfMemory issues, oversized arrays, unbounded lists, etc., This blog will list of the 9 types of OutOfMemoryErrors, what are their causes & solutions in detail.
4. Unified RCA
Root Cause Analysis provides a detailed analysis of incident summary, cause of the issue, how to prevent them to reoccur, who is responsible for those actions. yCrash provides a holistic RCA report by using its own automated tools like GCeasy, fastThread, HeapHero.
How Memory Analysis strengthens DevOps Collaboration
- Insights of memory diagnostic reports enhanced shared visibility
- yCrash integrated automated diagnostic approach dramatically reduces MTTR from days to hours
- Gives better on-call experience
- Provides a continuous learning culture for both dev and ops team
Impact of Memory Analysis on Performance ROI
Memory analysis has a direct impact on improving Performance ROI through
- Significant reduction in infrastructure cost by proper identification of RAM over allocation, inefficient data structure and memory leaks
- Reduced MTTR saves Engineering hours
- Proactive memory analysis yields higher customer satisfaction
Summary
Memory analysis becomes an integral part of devops, where their key performance ROI can be enhanced. Deployment of all-in-one bundle automated tool like yCrash gives super magic power for the managers of devops to empower engineers to build resilient systems in an increasingly performance driven digital world
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