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As an open-source project, OpenTelemetry sets standards for telemetry data sets and works with a wide range of systems and platforms to collect and export telemetry data to backend systems. Second, it enables efficient and effective correlation and comparison of data between various sources. OpenTelemetry Collector 1.0
Because opensource software (OSS) is taking over the world, optimizing opensource contributions is becoming an essential competitive strategy. However, opensource is not a panacea. These considerations are important if developers want to maximize the impact of their contributions to opensource projects.
Ready to transition from a commercial database to opensource, and want to know which databases are most popular in 2019? We broke down the data by opensource databases vs. commercial databases: OpenSource Databases. Popular examples of opensource databases include MySQL, PostgreSQL and MongoDB.
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.
A good Kubernetes SLO strategy helps teams manage and make containerized workloads more efficient. Kubernetes is a widely used opensource system for container orchestration. Efficient coordination of resource usage, requests, and allocation is critical.
In today's data-driven world, efficient data processing plays a pivotal role in the success of any project. Apache Spark , a robust open-source data processing framework, has emerged as a game-changer in this domain.
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?
With the evolution of modern applications serving increasing needs for real-time data processing and retrieval, scalability does, too. One such open-source, distributed search and analytics engine is Elasticsearch, which is very efficient at handling data in large sets and high-velocity queries.
SVT-AV1: open-source AV1 encoder and decoder by Andrey Norkin , Joel Sole , Mariana Afonso , Kyle Swanson, Agata Opalach , Anush Moorthy , Anne Aaron SVT-AV1 is an open-source AV1 codec implementation hosted on GitHub [link] under a BSD + patent license.
Scalable Video Technology (SVT) is Intel’s opensource framework that provides high-performance software video encoding libraries for developers of visual cloud technologies. The standard specification describes in minute detail how a video bitstream should be processed in order to produce displayable video frames.
Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. What Exactly is Greenplum? Greenplum Advantages.
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. Dynatrace now fully supports them.
RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. RabbitMQ follows a message broker model with advanced routing, while Kafkas event streaming architecture uses partitioned logs for distributed processing. What is RabbitMQ?
Until recently, improvements in data center power efficiency compensated almost entirely for the increasing demand for computing resources. For example, reporting jobs can process monthly data without running exactly at the end of the month. However, this trend is now reversing. The time to act is now.
As a result, requests are uniformly handled, and responses are processed cohesively. This data is processed from a real-time impressions stream into a Kafka queue, which our title health system regularly polls. The request schema for the observability endpoint.
The use of opensource databases has increased steadily in recent years. Past trepidation — about perceived vulnerabilities and performance issues — has faded as decision makers realize what an “opensource database” really is and what it offers. What is an opensource database?
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. With OpenPipeline, you can easily collect data from Dynatrace OneAgent®, opensource collectors such as OpenTelemetry, or other third-party tools.
Migrating a proprietary database to opensource is a major decision that can significantly affect your organization. It’s a complex process involving various factors and meticulous planning. Flexibility and scalability Opensource databases provide much greater flexibility regarding customization and configuration.
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Deploying software in Kubernetes is often viewed as a straightforward process—just use kubectl or a GitOps solution like ArgoCD to deploy a YAML file, and you’re all set, right? Conclusion Keptn empowers DevOps teams to conquer the Kubernetes deployment challenge confidently, ensuring smoother and more efficient deployments.
DevOps platform engineers are responsible for cloud platform availability and performance, as well as the efficiency of virtual bandwidth, routers, switches, virtual private networks, firewalls, and network management. Version control system and source code management with end-to-end DevOps platform and cloud-hosted Git services.
On top of that, our CNCF OpenSource project, Keptn , brings cloud automation use cases around progressive delivery and operations to our users enabling our Dynatrace customers to establish a NoOps culture like we have at Dynatrace engineering. It happened in June 2020. Houston, we have a problem! Can we fix it? Yes, we can!
DevSecOps teams can address this unsettling tradeoff by automating processes throughout the SDLC, centralizing application configuration with a shared set of tools, and using observability platforms to gain visibility into code-quality lapses, security gaps, and other software development issues.
Kubernetes is a widely used opensource system for container orchestration. However, they can also be used to monitor optimization processes effectively. Efficient coordination among resource usage, requests, and allocation is critical. It provides insights into how efficiently the blocked resources are being utilized.
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.
The manual testing process has been replaced by automated testing during recent years. Selenium automation testing increases the effectiveness and efficiency of the testers and allows them to leverage various benefits at the same time. Me looking for the perfect match for automation testing.
Container security is the practice of applying security tools, processes, and policies to protect container-based workloads. Application developers commonly leverage open-source software when building containerized applications. 1] And unfortunately, open-source software is often fraught with security vulnerabilities.
Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data.
Thanks to technological advancements and the accessibility of open-source tools, gathering and analyzing data from IoT devices has become easier than ever before. In this tutorial, we will guide you through the process of setting up a monitoring system for IoT device data.
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Opensource has also become a fundamental building block of the entire cloud-native stack. While leveraging cloud-native platforms, open-source and third-party libraries accelerate time to value significantly, it also creates new challenges for application security.
AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. What is AIOps, and how does it work?
OpenTelemetry is an opensource observability project that encompasses a set of APIs, libraries, agents, and instrumentation standards. Using OpenTelemetry, developers can collect and process telemetry data from applications, services, and systems. Employ efficient sampling. What is OpenTelemetry? Contextualize data.
The cloud-based, on-demand execution model of serverless architecture helps teams innovate more efficiently and effectively by removing the burden of managing the underlying infrastructure. To get a handle on observability, teams often adopt open-source observability tools, such as Prometheus, OpenTelemetry , and StatsD.
IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA automates repetitive cloud operations tasks and streamlines the flow of analytics into decision-making processes.
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. The fluidity of this process is possible through automation tools compatible with Kubernetes.
At financial services company, Soldo, efficiency and security by design are paramount goals. This is especially true as organizations rely more on diverse and nimble cloud-native and opensource technologies. This is especially true as organizations rely more on diverse and nimble cloud-native and opensource technologies.
Kubernetes has become the leading container orchestration platform for organizations adopting opensource solutions to manage, scale, and automate application deployment. Kubernetes is an opensource container orchestration platform for managing, automating, and scaling containerized applications. What is Kubernetes?
The risk of impact from an existing known vulnerability also depends on whether certain processes are using the vulnerable parts of a software component. Vulnerable function monitoring Tracking vulnerable opensource software components efficiently is one of the most important pillars of managing attack surfaces.
Kubernetes is an open-source orchestration engine for containerized applications that help to automate processes such as scaling, deployments, and management with greater efficiency. . Open Dynatrace in your browser and go to Infrastructure > Kubernetes and select Connect manually. What is Kubernetes?
DevOps seeks to accomplish smooth and efficient software creation, delivery, monitoring, and improvement by prioritizing agility and adaptability over rigid, stage-by-stage development. With the help of open-source solutions and agile APIs, teams can now deliver and maintain code more efficiently than ever.
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After a decade of helping companies manage container orchestration, Kubernetes, the opensource container platform, has established itself as a mature enterprise technology. In addition, their logs-heavy approach to analysis made scaling processes complex and costly. Cost efficiency. Complete visibility for Kubernetes.
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