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One of the toughest decisions your software development team may face as you scale is deciding between keeping your current codebase and rebuilding on new software architecture. Rethink, Restructure, and Rebuild. Rethink, Restructure, and Rebuild. Sometimes it takes less effort in terms of time and money to build a solution from scratch.
Observability industry themes to watch Perhaps the most significant industry trend is the shift from traditional, on-premises environments to multicloud or cloud-native architectures. The post Using modern observability to chart a course to successful digital transformation appeared first on Dynatrace news.
As a result, organizations are weighing microservices vs. monolithic architecture to improve software delivery speed and quality. Traditional monolithic architectures are built around the concept of large applications that are self-contained, independent, and incorporate myriad capabilities. What is monolithic architecture?
Today, I want to share my experience working with Zabbix, its architecture, its pros, and its cons. Over the course of five years, while working on the project, we went through several system upgrades until we finally transitioned to Zabbix 4.0 It also allows for some advanced features, such as problem prediction.
Grail architectural basics. The aforementioned principles have, of course, a major impact on the overall architecture. A data lakehouse addresses these limitations and introduces an entirely new architectural design. It’s based on cloud-native architecture and built for the cloud. But what does that mean?
New Architectures (this post). Cloud seriously impacts system architectures that has a lot of performance-related consequences. Auto-scaling is often presented as a panacea for performance problems, but, even if it is properly implemented (which is, of course, better to be tested), it just assigns a price tag for performance.
I should start by saying this section does not offer a treatise on how to do architecture. We often say "blueprints," but that's another metaphor borrowed from the original field, and of course we don't make actual blueprints. Vitruvius and the principles of architecture. Everyone who goes to architecture school learns his work.
Of course, we believe in the transformative potential of NN throughout video applications, beyond video downscaling. Our approach to NN-based video downscaling The deep downscaler is a neural network architecture designed to improve the end-to-end video quality by learning a higher-quality video downscaler.
The fact is, Reliability and Resiliency must be rooted in the architecture of a distributed system. The email walked through how our Dynatrace self-monitoring notified users of the outage but automatically remediated the problem thanks to our platform’s architecture. And that’s true for Dynatrace as well.
Evaluating these on three levels—data center, host, and application architecture (plus code)—is helpful. Application architectures might not be conducive to rehosting. Of course, you need to balance these opportunities with the business goals of the applications served by these hosts. Unfortunately, it’s not that simple.
The need for fast product delivery led us to experiment with a multiplatform architecture. This approach works well for us for several reasons: Our Android and iOS studio apps have a shared architecture with similar or in some cases identical business logic written on both platforms. Networking Hendrix interprets rule set(s)?—?remotely
Lightweight architecture. The overall architecture – including the consolidated Dynatrace API – is shown below: Different problem visualizations build on top of a lightweight backend that uses the consolidated Dynatrace API. Getting the problem status of all environments has to be efficient. js framework. js framework.
Hyperscale is the ability of an architecture to scale appropriately as increased demand is added to the system. Organizations, and teams within them, need to stay the course, leveraging multicloud platforms to meet the demand of users proactively and proficiently, as well as drive business growth. But what does that look like?
Over the course of several posts, we have seen how, as a result of the evolution of application architectures, new needs arise in the field of testing. We have focused on a specific one. We have seen that we have Contract Testing within our reach, with different approaches and tools that allow us to address this specific need.
Thanks to the simplicity of our microservice architecture, we were able to quickly identify that our MongoDB connection handling was the root cause of the memory leak. And of course: no more OOMs. To fix the memory leak, we leveraged the information provided in Dynatrace and correlated it with the code of our event broker.
Over the course of the last year, we’ve incrementally extended the coverage of security policies to provide a common authorization mechanism for the entire Dynatrace platform. If so, check out our Extend flexible and granular access management for teams blog post to understand the basic architecture and have a look at our documentation.
The implications of software performance issues and outages have a significantly broader impact than in the past—with the potential to negatively impact revenue, customer experiences, patient outcomes, and, of course, brand reputation. Ideally, resiliency plans would lead to complete prevention.
According to IBM , application modernization takes existing legacy applications and modernizes their platform infrastructure, internal architecture, or features. Of course, cloud application modernization solutions are not always focused on rebuilding from the ground up. Why should organizations modernize applications?
“Because of the uncertainty of the times and the likely realities of the ‘new normal,’ more and more organizations are now charting the course for their journeys toward cloud computing and digital transformation,” wrote Gaurav Aggarwal in a Forbes article the impact of COVID-19 on cloud adoption.
For this visualization I used the same backend architecture as for the real-time visualization I presented previously. This might be disputable, of course, but from an operations perspective one could question: “Are problems that only last for a couple of minutes worth investigating? ” Lessons learned.
Statoscope: A Course Of Intensive Therapy For Your Bundle. Statoscope: A Course Of Intensive Therapy For Your Bundle. That’s why I made effort to architecturally sculpt each piece of the toolkit (it wasn’t for nothing that said it was a toolkit) so that it functions as a plugin, not as something hardcoded. Sergey Melukov.
As digital transformation accelerates, organizations turn to hybrid and multicloud architectures to innovate, grow, and reduce costs. But the complexity and scale of multicloud architecture invites new enterprise challenges. Protection means securing complex, distributed and high-velocity cloud architectures,” the article continued.
Cloud-native software design, much like microservices architecture, is founded on the premise of speed to delivery via phases, or iterations. Of course, each valuable innovation will eventually have a blog post of its own, explaining how Dynatrace can further solve your Kubernetes-observability challenges.
Distributing accounts across the infrastructure is an architectural decision, as a given account often has similar usage patterns, languages, and sizes for their Lambda functions. Of course, this requires a VM that provides rock-solid isolation, and in AWS Lambda, this is the Firecracker microVM. The virtual CPU is turned off.
IT performance problems increase with cloud-native architectures. 76% said they don’t have complete visibility into application performance in cloud-native architectures. Of course, you need Dynatrace®. More specifically, our report found: 49% of CIOs are concerned IT performance problems will cause a loss in revenue.
Hyperconverged infrastructure (HCI) is an IT architecture that combines servers, storage, and networking functions into a unified, software-centric platform to streamline resource management. In a standard server or resource model, silos are par for the course. That’s where hyperconverged infrastructure, or HCI, comes in.
Of course, this comes with all the benefits that Dynatrace is known for: the Davis® AI causation engine and entity model, automatic topology detection in Smartscape, auto-baselining, automated error detection, and much more. Understand Istio, the Kubernetes native service mesh.
From a technical standpoint, I think multi-threaded architecture is quite superior; the cost of process context switch is a lot more expensive than thread context switch. Should PostgreSQL become multi-threaded ? — Peter Zaitsev (@PeterZaitsev) June 12, 2023 I am very excited to see this discussion finally happening!
Increasingly, organizations are turning to observability solutions to get visibility into their dynamic container-based architectures and hybrid-cloud environments. But of course, there are metrics for which this assumption does not hold. While observing is critical, the real value comes with the capacity for predictive AIOps.
Of course, development teams need to understand how their code behaves in production and whether any issues need to be fixed. Pre-built custom dashboards enable the team to share the hourly billing data with development teams, giving them insights into how architecture and design decisions drive costs.
Cloud-based application architectures commonly leverage microservices. In response to this trend, open source communities birthed new companies like WSO2 (of course, industry giants like Google, IBM, Software AG, and Tibco are also competing for a piece of the API management cake).
Computer architecture is an important and exciting field of computer science, which enables many other fields (eg. For those of us who pursued computer architecture as a career, this is well understood. In most curriculums, undergrad students do not have much exposure to computer architecture. Why is that? Lack of Exposure.
Introducing Metrics on Grail Despite their many advantages, modern cloud-native architectures can result in scalability and fragmentation challenges. For more complex cloud-native architectures, adding more services and applications leads to a massive increase in the volume of collected traces.
From an architectural perspective, the system should be able to undertake real-time analysis of various formats of logs, and of course, be scalable to support the huge and ever-enlarging data size.
But in today’s fast-changing technology world driven by IoT, microservice based architectures, mobile app integration, automation, and containerization, modern businesses are faced with API security issues more than ever. They are, of course, not a complete solution, as they can be intercepted like any other network traffic.
Of course, if d is not a power of two, 2 N / d cannot be represented as an integer. I believe that all optimizing C/C++ compilers know how to pull this trick and it is generally beneficial irrespective of the processor’s architecture. The idea is not novel and goes back to at least 1973 (Jacobsohn).
At Dynatrace we live and breathe the concept of “Drink Your Own Champagne” (DYOC), so of course, I want to use Dynatrace to monitor my apps. App architecture. First, let’s explore the architecture of these apps: BizOpsConfigurator. But these are not your traditional apps; there’s nowhere to install OneAgent.
Other distributions like Debian and Fedora are available as well, in addition to other software like VMware, NGINX, Docker, and, of course, Java. We anticipate massive growth in the popularity of this architecture in the coming quarters, driven additionally by companies’ push for cost reductions.
That definition is applicable to any discipline, including functional programming and (of course) architecture. Design patterns attempt to name for solutions to problems that you see every day; naming the solution allows you to talk about it.
Especially in dynamic microservices architectures, distributed tracing is an essential component of efficient monitoring, application optimization, debugging, and troubleshooting. As the popularity of microservices architecture increases, many more teams are getting involved with the delivery of a single product feature.
Despite the drive in some quarters to make microservice architectures the default approach for software, I feel that due to their numerous challenges, adopting them still requires careful thought. They are an architectural approach, not the architectural approach. Where microservices don’t work well.
Dieter Landenahuf, a senior ACE Engineer at Dynatrace, built Jenkins pipelines for new microservice architectures by creating templates and copying, pasting, and modifying them slightly. Charting the course with Keptn. Limits of scripting for DevOps and SRE. Classic automation has limits.
Sysperf provides balanced coverage of models, theory, architecture, observability tools (traditional and tracing), experimental tools, and tuning. The BPF tools book focuses on BPF tracing tools only, with brief summaries of architecture and traditional tools. Which book should you buy?
Of course, much like the grapes, no two organizations are the same; how they adapted; how they took the challenge head-on; and how they changed their focus. Initially, there was an expectation that remote working would make this almost impossible, especially as teams were used to going into a room to whiteboard development and architecture.
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