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Site reliability engineering (SRE) plays a vital role in ensuring Java applications' high availability, performance, and scalability. This discipline merges software engineering and operations, aiming to create a robust infrastructure that supports seamless user experiences.
As a Software Engineer, the mind is trained to seek optimizations in every aspect of development and ooze out every bit of available CPU Resource to deliver a performing application. Considering all aspects and needs of current enterprise development, it is C++ and Java which outscore the other in terms of speed. Ahem, Slow!
Cloud-native technologies and microservice architectures have shifted technical complexity from the source code of services to the interconnections between services. Deep-code execution details. You get code-level insights into application code without code changes. Dynatrace news. The app is powered by Kubernetes.
This first step clearly shows that the code that powers getFamilyCondition is using a lot of CPU – much more than any other of the top services combined! It can be your own code, 3 rd party code or your runtime that executes for certain tasks such as Garbage Collection. So – we found the culprit!
Our Cluster Performance Engineering Team in collaboration with our Autonomous Cloud Enablement (ACE) and development teams quickly identified the root cause and fixed the problem in no time! And the code-level root cause information is what makes troubleshooting easy for developers. Step 3: Identifying root-cause in code.
Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. To achieve high reliability, one needs to keep a wary eye on the code quality of projects developed for this area. This engine is written in Java and Scala.
It warns software engineers of bugs in newly-implemented code and regressions in existing code, before it is merged. It also … The post Handling Flaky Unit Tests in Java appeared first on Uber Engineering Blog. Unit testing forms the bedrock of any Continuous Integration (CI) system.
Recently, a critical vulnerability was discovered in Apache Struts, a widely used Java-based web application framework. This vulnerability, published as CVE-2024-53677 on December 11, 2024, affects the file upload mechanism, allowing for path traversal and potential remote code execution.
Broken Apache Struts 2: Technical Deep Dive into CVE-2024-53677The vulnerability allows attackers to manipulate file upload parameters, possibly leading to remote code execution. Introduction Apache Struts 2 is a widely used Java framework for web applications, valued for its flexibility and Model-View-Controller (MVC) architecture.
The convention I’m referring to is naming Java classes with a trailing Impl. It’s as restrictive as the Sith philosophy, limiting the potential of your code because it implicitly suggests there should only be one implementation of that interface. May the Force (and good coding practices) be with you! This is a trap!
DevOps teams, SREs (site reliability engineers), platform teams, and SecOps teams aren’t always working from a common source of truth: SAST tools (static application security testing) provide scanning code for vulnerabilities. Dynatrace extends its Runtime Vulnerability Analysis to Go on top of Java ,NET , Node.js
In cloud-native application stacks, everything is code. Dynatrace entered the Application Security market with automatic and continuous protection for Java workloads. and Java are the most popular languages within Kubernetes environments. Now, engineers can use a direct link to the affected container images as well.
Although IT teams are thorough in checking their code for any errors, an attacker can always discover a loophole to exploit and damage applications, infrastructure, and critical data. Malicious actors can execute any code on the attacked system, for example, to access sensitive configuration data.
Dynatrace has been building automated application instrumentation—without the need to modify source code—for over 15 years already. Driving the implementation of higher-level APIs—also called “typed spans”—to simplify the implementation of semantically strong tracing code. What Dynatrace will contribute.
Fully automated code-level visibility. Apart from its best-in-class observability capabilities like distributed traces, metrics, and logs, Dynatrace OneAgent additionally provides automatic deep code-level insights for Java,NET, Node.js, PHP, and Golang, without the need to change any application code or configuration.
In May 2023 the critical vulnerability CVE-2020-36641 in the Java library aXMLRPC was published in the National Vulnerability Database (NVD). To what extent attacks are possible depends on the Java version and other environmental factors. This PoC has been validated for versions 1.12.1 Why is the CVE-2020-36641 vulnerability not fixed?
A new critical remote code execution (RCE) vulnerability was disclosed on October 13, 2022. A remote code execution vulnerability is a cyberattack an attacker can remotely execute commands on a user’s computing device. The vulnerability affects the Apache Commons Text library. CVE-2022-42889 not as critical as Log4Shell.
One of these solutions is Micrometer which provides 17+ pre-instrumented JVM-based frameworks for data collection and enables instrumentation code with a vendor-neutral API. Spring Boot, on the other hand, is a Java framework for building cloud-native Java applications. No cumbersome endpoint URL and token management.
Code changes are often required to refine observability data. This results in site reliability engineers nudging development teams to add resource attributes, endpoints, and tokens to their source code. Thus, measuring application performance becomes an unnecessarily frustrating coordination effort between teams.
While memory allocation analysis can show wasteful or inefficient code, it can also reveal different problems, one of which we’ll examine in this blog post. We recently extended the pre-shipped code-level API definitions to group logical parts of our code so they’re consistently highlighted in all code-level views.
“Engineers today lack an easy way to track the tokens and prompt usage of their LLM applications in production. Combining Dynatrace with Traceloop’s OpenLLMetry addresses the heterogeneity challenge by supporting a range of popular LLMs, prompt engineering, and chaining frameworks. Maintained under the Apache 2.0
Without efficient, reliable, and repeatable software updates, engineers need to redirect their focus from developing new features to managing and debugging their deployments. Thousands of Amazon developers use Apollo each day to deploy a wide variety of software, from Java, Python, and Ruby apps, to HTML web sites, to native code services.
This was all a spare time project, as my day job at Netflix at that time was as a director level manager of a team working on personalization code in Java, and it wasnt my job to write the codemyself. One of the Javaengineers on my teamJian Wujoined me to help figure out the API. The code is still up on github.
There are three current underlying reasons for the platform engineering meme today. The next layer is defined by the languages you want to use, Java, Python, Go, , Javascript, Rust etc, and the ecosystem of library functions you bought from a vendor or downloaded.
The solution we use within the Netflix Studio Engineering is protobuf FieldMask. link] When the protobuf compiler (protoc) compiles this message definition, it creates the code in the language of your choice (Java in our example). Let’s explore this code sample in more detail. (1) Our protobuf message definition (.proto
focused on technology coverage, building on the flexibility of JMX for Java and Python-based coded extensions for everything else. While Python code can address most data acquisition and ingest requirements, it comes at the cost of complexity in implementation and use-case modeling. Dynatrace Extensions 1.0 Extensions 2.0
In a recent webinar , Dynatrace DevOps activist Andi Grabner and senior software engineer Yarden Laifenfeld explored developer observability. Why is developer observability important for engineers? But developers need code-level visibility and code-level data.” Observability is about answering questions,” said Laifenfeld.
You can ask Davis, the Dynatrace AI engine , to correlate CPU usage against other signals. In this case, Davis finds that a Java Spring Micrometer metric called Failed deliveries is highly correlated with CPU spikes. Seeing is believing You can find out more about Dynatrace and Red Hat here. Try it out with a free trial.
The green frames are the actual instructions running on the AI or GPU accelerator, aqua shows the source code for these functions, and red (C), yellow (C++), and orange (kernel) show the CPU code paths that initiated these AI/GPU programs. The gray "-" frames just help highlight the boundary between CPU and AI/GPU code.
Teams are embracing new technologies and continuously deploying code. But what if you could see what’s running in production in real-time, continuously analyzing all services for vulnerabilities, and prioritizing those based on what code is called? This automation is powered by Dynatrace’s AI engine, Davis.
According to the 2022 CISO Research Report , only 25% of respondents’ security teams “can access a fully accurate, continuously updated report of every application and code library running in production in real-time.” Undetected, the compromised code could allow attackers to access data they’re not authorized to have.
In the Advancing DevOps and DevSecOps track, sessions aim to help security pros, developers, and engineers as they brace for new threats that are costly and time-consuming to address. The vulnerability is located in Log4j 2, an open-source Apache Java software used to run logging services in a host of front-end and backend applications.
Managing Auto-Instrumentation in Pods The Operator automatically injects and configures auto-instrumentation for your applications, which enables you to collect telemetry data without modifying your source code. Instrumentation Instrumentation is the process of adding code to software to generate telemetry signalslogs, metrics, and traces.
By leveraging the AWS Lambda Extensions API , Dynatrace brings the unique value of its Davis AI-engine for fully automatic root cause analysis to AWS Lambda. This means, you don’t need to change even a single line of code in the serverless functions themselves. and Python via traces. Improved mapping and topology detection.
Soon we had hundreds of engineers contributing directly to the API on a daily basis. This gives us access to Netflix’s Java ecosystem, while also giving us the robust language features such as coroutines for efficient parallel fetches, and an expressive type system with null safety.
For years, the debate has raged on regarding which programming language is better, Java or Scala. While some argue that just because Java is older it is better, others believe Scala is better for a variety of reasons. In essence, Java is classified as an object oriented programming language. The Size and Quality of the Code.
Application security is a software engineering term that refers to several different types of security practices designed to ensure applications do not contain vulnerabilities that could allow illicit access to sensitive data, unauthorized code modification, or resource hijacking. Dynatrace news.
Many Site Reliability Engineers could do without the frustrations of managing virtual or bare-metal compute nodes. Dynatrace news. Though serverless platforms relieve them from this burden, such platforms are built using Kubernetes alternatives that require different APIs, orchestration tools, and observability requirements.
This drive for speed has a cost: 22% of leaders admit they’re under so much pressure to innovate faster that they must sacrifice code quality. In addition, 27% of IT and DevOps teams’ time is invested in manual CI/CD tasks such as detecting code quality issues, which reduces time spent on innovation. What is DevOps?
It is known for its flexibility and large feature set, as well as supporting databases utilizing a Java Database Connectivity (JDBC) driver, rendering it a default tool for both DBAs and developers. Pros: Powerful query editor with intelligent code completion. Lacks some advanced coding and debugging tools available in other products.
Lack of context —most vulnerability scanners don’t provide runtime context and key information like whether vulnerable code is used at runtime. Starting with Dynatrace version 1.225 and OneAgent version 1.207, you can detect runtime vulnerabilities and assess risks across Java, Node.js,NET, How to get started.
Log4Shell is a software vulnerability in Apache Log4j 2 , a popular Java library for logging information in applications. The vulnerability enables a remote attacker to execute arbitrary code on a service on the internet if the service runs certain versions of Log4j 2. Coordination and communication.
On the Android team, while most of our time is spent working on the app, we are also responsible for maintaining this backend that our app communicates with, and its orchestration code. This allowed Android engineers to have much more control and observability over how we get our data. Java…Script? It was a Node.js
It is not an analytics engine, and it doesn’t capture deeper observability signals such as CPU profiling, thread analysis, or memory location profiling. Users can add the APIs manually to their code to define exactly what needs to be measured and monitored continuously after the code is deployed for maintenance purposes.
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