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Why manual audits and custom scripts fall short for Kubernetes security posture management In the dynamic and complex world of Kubernetes, relying on manual audits, custom scripts, and general-purpose security tools is no longer enough to achieve efficient security posture management. Processes are time-intensive. Reactivity.
A production bug is the worst; besides impacting customer experience, you need special access privileges, making the process far more time-consuming. It also makes the process risky as production servers might be more exposed, leading to the need for real-time production data. This cumbersome process should not be the norm.
In this blog post, we will see how Dynatrace harnesses the power of observability and analytics to tailor a new experience to easily extend to the left, allowing developers to solve issues faster, build more efficient software, and ultimately improve developer experience!
Business processes support virtually all aspects of an organizations operations. Theyre often categorized by their function; core processes directly create customer value, support processes increase departmental efficiency, and management processes drive strategic goals and compliance.
In today's data-driven world, organizations need efficient and scalable data pipelines to process and analyze large volumes of data. Medallion Architecture provides a framework for organizing data processing workflows into different zones, enabling optimized batch and stream processing.
But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. With the Dynatrace modern observability platform, teams can now use intuitive, low-code/no-code toolsets and causal AI to extend answer-driven automation for business, development and security workflows.
A business process is a collection of related, usually structured tasks or steps, performed in sequence, that achieve a defined business goal. Tasks may be manual or automatic, and many business processes will include a combination of both. Make better decisions by providing managers with real-time data about the business.
Most of these leverage the unique capability of Dynatrace OneAgent® to extract business data from in-flight application payloads — without writing any code. Dynatrace OpenPipeline is a new stream processing technology that ingests and contextualizes data from any source. Business process monitoring and optimization.
They now use modern observability to monitor expanding cloud environments in order to operate more efficiently, innovate faster and more securely, and to deliver consistently better business results. Further, automation has become a core strategy as organizations migrate to and operate in the cloud. What is a data lakehouse?
The VS Code extension Dynatrace Apps is here to streamline your development process and simplify app building. Now you can easily query live data directly within VS Code using the Dynatrace Query Language (DQL). Sound familiar? This aids in effectively handling execution, loading, and error states.
This demand for rapid innovation is propelling organizations to adopt agile methodologies and DevOps principles to deliver software more efficiently and securely. But when and how does DevOps monitoring fit into the process? And how do DevOps monitoring tools help teams achieve DevOps efficiency? Lost efficiency.
Code review is a technique that can improve the quality of a codebase by having multiple developers look for bugs and other problems before passing them on to others. Manual code reviews are costly and time-consuming, which is why many development teams use automated tools to do this work.
The IT world is rife with jargon — and “as code” is no exception. “As code” means simplifying complex and time-consuming tasks by automating some, or all, of their processes. ” While this methodology extends to every layer of the IT stack, infrastructure as code (IAC) is the most prominent example.
This growth was spurred by mobile ecosystems with Android and iOS operating systems, where ARM has a unique advantage in energy efficiency while offering high performance. Energy efficiency and carbon footprint outshine x86 architectures The first clear benefit of ARM in the enterprise IT landscape is energy efficiency.
This is known as “security as code” — the constant implementation of systematic and widely communicated security practices throughout the entire software development life cycle. To mitigate security risks, comply with regulations, and align with good governance requires a coordinated effort among people, processes, and technology.
Moreover, the OpenTelemetry Collector can measure service span durations, categorized by span names, span kinds, and status codes. This self-monitoring aspect is crucial for maintaining the health and efficiency of the Collector itself, ensuring that it can handle the demands of large-scale data collection and processing without degradation.
One of the more popular use cases is monitoring business processes, the structured steps that produce a product or service designed to fulfill organizational objectives. By treating processes as assets with measurable key performance indicators (KPIs), business process monitoring helps IT and business teams align toward shared business goals.
This allows teams to sidestep much of the cost and time associated with managing hardware, platforms, and operating systems on-premises, while also gaining the flexibility to scale rapidly and efficiently. REST APIs, authentication, databases, email, and video processing all have a home on serverless platforms. The Serverless Process.
Adding Dynatrace runtime context to security findings allows smarter prioritization, helps reduce the noise from alerts, and focuses your DevSecOps teams on efficiently remedying the critical issues affecting your production environments and applications. The main categories are detections, vulnerabilities, and compliance misconfigurations.
Introducing sufficient jitter to the flush process can further reduce contention. By creating multiple topic partitions and hashing the counter key to a specific partition, we ensure that the same set of counters are processed by the same set of consumers. This process can also be used to track the provenance of increments.
HashiCorp’s Terraform is an open-source infrastructure as a code software tool that provides a consistent CLI workflow to manage hundreds of cloud services. With this integration, Dynatrace customers can now leverage Terraform to manage their monitoring infrastructure as code,” said Asad Ali, Senior Director of Sales Engineering at Dynatrace.
Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. The Netflix video processing pipeline went live with the launch of our streaming service in 2007. The Netflix video processing pipeline went live with the launch of our streaming service in 2007.
Here’s how Dynatrace can help automate up to 80% of technical tasks required to manage compliance and resilience: Understand the complexity of IT systems in real time Proactively prevent, prioritize, and efficiently manage performance and security incidents Automate manual and routine tasks to increase your productivity 1.
This leads to a more efficient and streamlined experience for users. Lastly, monitoring and maintaining system health within a virtual environment, which includes efficient troubleshooting and issue resolution, can pose a significant challenge for IT teams. Instead, they interact with the applications that are hosted on Hyper-V.
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. This blog post dissects the vulnerability, explains how Struts processes file uploads, details the exploit mechanics, and outlines mitigation strategies.
After optimizing containerized applications processing petabytes of data in fintech environments, I've learned that Docker performance isn't just about speed it's about reliability, resource efficiency, and cost optimization. We can fix that with this code below: Let's dive into strategies that actually work in production.
by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.
When you set up user actions in your code, OneAgent automatically links associated web requests to those user actions. Additionally, it exposes API calls to the Flutter code and forwards these API calls to OneAgent for iOS/Android. OneAgent for mobile apps is specific to iOS and Android.
Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. Data is then dynamically routed into pipelines for further processing. Such transformations can reduce storage costs by 99%.
Indeed, according to one survey, DevOps practices have led to 60% of developers releasing code twice as quickly. But increased speed creates a tradeoff: According to another study, nearly half of organizations consciously deploy vulnerable code because of time pressure. Increased adoption of Infrastructure as code (IaC).
CI/CD and Its Importance We all know what CI/CD is and how it fosters a sense of collaboration among teams and enables them to deliver high-quality software efficiently and reliably.
CI/CD is a series of interconnected processes that empower developers to build quality software through well-aligned and automated development, testing, delivery, and deployment. Together, these practices ensure better collaboration and greater efficiency for DevOps teams throughout the software development life cycle.
Dynatrace does this by automatically creating a dependency map of your IT ecosystem, pinpointing the technologies in your stack and how they interact with each other, including servers, processes, application services, and web applications across data centers and multicloud environments. asc | fields `Host`, `Recently Restarted?
The DevOps playbook has proven its value for many organizations by improving software development agility, efficiency, and speed. This method known as GitOps would also boost the speed and efficiency of practicing DevOps organizations. Development teams use GitOps to specify their infrastructure requirements in code.
Centralization of platform capabilities improves efficiency of managing complex, multi-cluster infrastructure environments According to research findings from the 2023 State of DevOps Report , “36% of organizations believe that their team would perform better if it was more centralized.” All this can be self-defined in the source code.
DevSecOps is a cross-team collaboration framework that integrates security into DevOps processes from the start rather than waiting to address security in a separate silo. DevOps has gained ground in recent years as a way to combine key operational principles with development cycles, recognizing that these two processes must coexist.
34% of CIOs say they sacrifice code security to deliver innovation quicker. For a closer look at the numbers from the Dynatrace, Snyk, and AWS joint research, plus more statistics on how automation increases efficiencies and reduces security risks, see the infographic report, Continuous delivery needs continuous security.
Evaluating these on three levels—data center, host, and application architecture (plus code)—is helpful. Most approaches focus on improving Power Usage Effectiveness (PUE), a data center energy-efficiency measure. energy-efficient data centers—cloud providers—achieve values closer to 1.2. A PUE of 1.0
One issue that often complicates this process is the "noisy neighbor" problem. Continuous instrumentation is critical to catching such matters as they emerge, and eBPF, with its hooks into the Linux scheduler with minimal overhead, enabled us to monitor run queue latency efficiently.
Apache Spark is a powerful open-source distributed computing framework that provides a variety of APIs to support big data processing. Broadcast variables can be used to efficiently distribute large read-only data structures, such as lookup tables, to worker nodes. This can significantly reduce network overhead and improve performance.
Still, while DevOps practices enable developer agility and speed as well as better code quality, they can also introduce complexity and data silos. More seamless handoffs between tasks in the toolchain can improve DevOps efficiency, software development innovation, and better code quality. They need automated DevOps practices.
The shift-left approach aims to ensure bugs and other issues are discovered and addressed early in the development process, leading to improved software quality and lower costs associated with late-stage troubleshooting. Today, engineers are spending an increasing amount of time developing and testing code in production-like environments.
By leveraging Dynatrace observability on Red Hat OpenShift running on Linux, you can accelerate modernization to hybrid cloud and increase operational efficiencies with greater visibility across the full stack from hardware through application processes.
This is a set of best practices and guidelines that help you design and operate reliable, secure, efficient, cost-effective, and sustainable systems in the cloud. The framework comprises six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.
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