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Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience.
However, your responsibilities might change or expand, and you need to work with unfamiliar data sets. Activate Davis AI to analyze charts within seconds Davis AI can help you expand your dashboards and dive deeper into your available data to extract additional information.
Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. This is where large-scale system migrations come into play.
What’s the problem with Black Friday traffic? But that’s difficult when Black Friday traffic brings overwhelming and unpredictable peak loads to retailer websites and exposes the weakest points in a company’s infrastructure, threatening application performance and user experience. Why Black Friday traffic threatens customer experience.
DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. On average, organizations use 10 different tools to monitor applications, infrastructure, and user experiences across these environments.
The Dynatrace Software Intelligence Platform gives you a complete Infrastructure Monitoring solution for the monitoring of cloud platforms and virtual infrastructure, along with log monitoring and AIOps. Ensure high quality network traffic by tracking DNS requests out-of-the-box. What’s next.
Cloud service providers (CSPs) share carbon footprint data with their customers, but the focus of these tools is on reporting and trending, effectively targeting sustainability officers and business leaders. Power usage effectiveness (PUE) is derived from data provided by the cloud providers and data center operators.
Accurately Reflecting Production Behavior A key part of our solution is insights into production behavior, which necessitates our requests to the endpoint result in traffic to the real service functions that mimics the same pathways the traffic would take if it came from the usualcallers. there is a dedicated collector.
Metadata and assets must be correctly configured, data must flow seamlessly, microservices must process titles without error, and algorithms must function as intended. Option 1: Log Processing Log processing offers a straightforward solution for monitoring and analyzing title launches.
With the pace of digital transformation continuing to accelerate, organizations are realizing the growing imperative to have a robust application security monitoring process in place. What are the goals of continuous application security monitoring and why is it important?
As businesses compete for customer loyalty, it’s critical to understand the difference between real-user monitoring and synthetic user monitoring. However, not all user monitoring systems are created equal. What is real user monitoring? Real-time monitoring of user application and service interactions.
In fact, according to a Dynatrace global survey of 1,300 CIOs , 99% of enterprises utilize a multicloud environment and seven cloud monitoring solutions on average. What is cloud monitoring? Cloud monitoring is a set of solutions and practices used to observe, measure, analyze, and manage the health of cloud-based IT infrastructure.
Over the last two month s, w e’ve monito red key sites and applications across industries that have been receiving surges in traffic , including government, health insurance, retail, banking, and media. Monitoring with ?the A deeper investigation into industry-specific data reveals several interesting findings. .
For cloud operations teams, network performance monitoring is central in ensuring application and infrastructure performance. Worse, a malicious attacker may gain access to the network, compromising sensitive application data. If the network is sluggish, an application may also be slow, frustrating users.
Scaling RabbitMQ ensures your system can handle growing traffic and maintain high performance. Youll also learn strategies for maintaining data safety and managing node failures so your RabbitMQ setup is always up to the task. Monitoring the cluster nodes preemptively addresses potential issues, ensuring the system operates smoothly.
In today’s data-driven world, businesses across various industry verticals increasingly leverage the Internet of Things (IoT) to drive efficiency and innovation. IoT is transforming how industries operate and make decisions, from agriculture to mining, energy utilities, and traffic management.
With Dynatrace actively managing business-critical applications, some of our globally distributed enterprise customers require Dynatrace Managed to continue operating even when an entire data center goes down. Near-zero RPO and RTO—monitoring continues seamlessly and without data loss in failover scenarios.
You’re not yet convinced there’s a real problem but you’re also aware that the clock is ticking as you dig through a mountain of data looking for clues. Our streaming teams need a monitoring system that enables them to quickly diagnose and remediate problems; seconds count! Regional traffic evacuations. So we built Telltale.
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. There are several ways Dynatrace monitors and alerts on the impact of service disruption. Ready to learn more? Fact #2: No significant impact on Dynatrace Users.
Dynatrace OneAgent is great for monitoring the full stack. You could of course create a custom device in Dynatrace and send data to it using our API or an ActiveGate extension. While this will give you a lot of information about the health of these components, sometimes a simple synthetic monitor is sufficient. Dynatrace news.
Throughout my career I’ve been asked several times by members of the ITOps teams, “Why end-user experience monitoring is critical”. So, I figured it’s about time I summarized the top reasons why you as an ITOps person need to look beyond your typical IT sources – logs, metrics and traces – which are these days known as Observability data.
Digital experience monitoring (DEM) allows an organization to optimize customer experiences by taking into account the context surrounding digital experience metrics. What is digital experience monitoring? DEM can give organizations business observability—insight into the effects of user experience on the bottom line.
Dynatrace and the Dynatrace Intelligent Observability Platform have added support for the newly introduced Amazon VPC Flow Logs to Amazon Kinesis Data Firehose. This support enables customers to define specific endpoint delivery of real-time streaming data to platforms such as Dynatrace. What is VPC Flow Logs? Why Dynatrace?
With its ability to handle large amounts of traffic and complex data, the Apollo router is quickly becoming a popular choice among developers seeking a reliable and efficient routing solution. With this integrated telemetry functionality, the Apollo router provides a streamlined and efficient performance monitoring solution.
Dynatrace Digital Experience Monitoring , as part of the Dynatrace Software Intelligence Platform, connects front-end monitoring and the outside-in user perspective with application performance to understand the impact of performance issues across your full stack on user experience and business outcomes. Virginia (Azure), N.
To do this, we devised a novel way to simulate the projected traffic weeks ahead of launch by building upon the traffic migration framework described here. New content or national events may drive brief spikes, but, by and large, traffic is usually smoothly increasing or decreasing.
With the world’s increased reliance on digital services and the organizational pressure on IT teams to innovate faster, the need for DevOps monitoring tools has grown exponentially. But when and how does DevOps monitoring fit into the process? And how do DevOps monitoring tools help teams achieve DevOps efficiency?
This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case.
Log data—the most verbose form of observability data, complementing other standardized signals like metrics and traces—is especially critical. As cloud complexity grows, it brings more volume, velocity, and variety of log data. When trying to address this challenge, your cloud architects will likely choose Amazon Data Firehose.
These resources generate vast amounts of data in various locations, including containers, which can be virtual and ephemeral, thus more difficult to monitor. These challenges make AWS observability a key practice for building and monitoring cloud-native applications. AWS monitoring best practices. And why it matters.
This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.
Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.
In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices.
Over the last year, Dynatrace extended its AI-powered log monitoring capabilities by providing support for all log data sources. We added monitoring and analytics for log streams from Kubernetes and multicloud platforms like AWS, GCP, and Azure, as well as the most widely used open-source log data frameworks.
Modern IT organizations are generating more data from more tools and technologies than ever. Data is proliferating in separate silos from containers and Kubernetes to open source APIs and software to serverless compute services, such as AWS and Azure. For this comprehensive monitoring in context, they had adopted Dynatrace.
RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. Both serve distinct purposes, from managing message queues to ingesting large data volumes.
The data locked in your log files can be a goldmine for your application developers, operations teams, and your enterprise as a whole. However, it can be complicated , expensive , or even impossible to set up robust observability that makes use of this data. Log format inconsistency makes it a challenge to access critical data.
Welcome back to our power dashboarding blog series , data enthusiasts! Our enhanced host monitoring dashboard that highlights disk usage includes AI forecasting for CPU usage. Query your data with natural language Davis CoPilot is an excellent virtual assistant that helps you create queries using natural language. Select Run.
Every image you hover over isnt just a visual placeholder; its a critical data point that fuels our sophisticated personalization engine. This nuanced integration of data and technology empowers us to offer bespoke content recommendations. This queue ensures we are consistently capturing raw events from our global userbase.
We recently announced Dynatrace Live Debugger , which gives developers unprecedented access to real-time data and runtime behavior insights. How can you tell if an algorithm or data source changed or a new feature flag worked? Test data collection Accurate test data can mean life or death.
OpenTelemetry , the open source observability tool, has become the go-to standard for instrumenting custom applications to collect observability telemetry data. For this third and final part of our series, we saved the best for last: How you can enhance telemetry data even more and with less effort on your end with Dynatrace OneAgent.
Dynatrace offers powerful and fully integrated synthetic monitoring capabilities to manage service level agreements (SLAs) of your web applications and APIs. With just a view clicks you can record and playback clickpaths of your most critical application paths or leverage HTTP monitors to monitor internal as wells external API endpoints.
Testing Strategies: A Summary Two key factors determined our testing strategies: Functional vs. non-functional requirements Idempotency If we were testing functional requirements like data accuracy, and if the request was idempotent , we relied on Replay Testing. In such cases, we were not testing for response data but overall behavior.
Service meshes are becoming increasingly popular in cloud-native applications as they provide a way to manage network traffic between microservices. Istio, one of the most popular service meshes, uses Envoy as its data plane. Distributed rate-limiting : Prevents abuse and protects the service from excessive requests.
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