This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
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.
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.
Applications and services are often slowed down by under-performing DNS communications or misconfigured DNS servers, which can result in frustrated customers uninstalling your application. While our competitors only provide generic traffic monitoring without artificial intelligence, Dynatrace automatically analyzes DNS-related anomalies.
An attacker has gained access through security misconfigurations in an API server, escalated privileges, and deployed cryptocurrency mining pods that consume massive resources. API server The API server is the gateway to your Kubernetes kingdom. An unprotected kubelet is like giving attackers direct access to your servers.
Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns. To overcome these challenges, we developed a holistic approach that builds upon our Data Gateway Platform. Data Model At its core, the KV abstraction is built around a two-level map architecture.
Before GraphQL: Monolithic Falcor API implemented and maintained by the API Team Before moving to GraphQL, our API layer consisted of a monolithic server built with Falcor. A single API team maintained both the Java implementation of the Falcor framework and the API Server. To launch Phase 1 safely, we used AB Testing.
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.
Initial access An attacker discovers an exposed Kubernetes API server during a routine scan. Misconfiguration : Exposed API server + overly permissive RBAC settings Attacker technique : The attacker uses automated tools to authenticate as the default service account and begins reconnaissance of the cluster resources.
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.
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.
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.
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. Readers who share our privacy concerns, please note, all the data we monitor is publicly available. . Monitoring with ?the
In my last blog , I’ve provided an example of this happening, whereby the traffic spiked and quadrupled the usual incoming traffic. These are all interesting metrics from marketing point of view, and also highly interesting to you as they allow you to engage with the teams that are driving the traffic against your IT-system.
In the past 15+ years, online video traffic has experienced a dramatic boom utterly unmatched by any other form of content. It must be said that this video traffic phenomenon primarily owes itself to modernizations in the scalability of streaming infrastructure, which simply weren’t present fifteen years ago.
Andreas Andreakis , Ioannis Papapanagiotou Overview Change-Data-Capture (CDC) allows capturing committed changes from a database in real-time and propagating those changes to downstream consumers [1][2]. No locks on tables are ever acquired, which prevent impacting write traffic on the source database. Writing events to any output.
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.
Andreas Andreakis , Ioannis Papapanagiotou Overview Change-Data-Capture (CDC) allows capturing committed changes from a database in real-time and propagating those changes to downstream consumers [1][2]. No locks on tables are ever acquired, which prevent impacting write traffic on the source database. Writing events to any output.
The F5 BIG-IP Local Traffic Manager (LTM) is an application delivery controller (ADC) that ensures the availability, security, and optimal performance of network traffic flows. Detect and respond to security threats like DDoS attacks or web application attacks by monitoring application traffic and logs.
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.
Incremental Backups: Speeds up recovery and makes data management more efficient for active databases. Faster Write Operations: Enhancements to the write-ahead log (WAL) processing double PostgreSQLs ability to handle concurrent transactions, improving uptime and data accessibility. Start your free trial today!
The massive volumes of log data associated with a breach have made cybersecurity forensics a complicated, costly problem to solve. As organizations adopt more cloud-native technologies, observability data—telemetry from applications and infrastructure, including logs, metrics, and traces—and security data are converging.
OpenTelemetry for Go provides developers with an observability framework for cloud-native software, allowing them to instrument, generate, collect, and export telemetry data for relevant services. Such additional telemetry data includes user-behavior analytics, code-level visibility, and metadata (including open-source data).
A standard Docker container can run anywhere, on a personal computer (for example, PC, Mac, Linux), in the cloud, on local servers, and even on edge devices. This opens the door to auto-scalable applications, which effortlessly matches the demands of rapidly growing and varying user traffic. What is Docker? Networking. Observability.
The Qualys Threat Research Unit (TRU) has discovered a Remote Unauthenticated Code Execution (RCE) vulnerability in OpenSSH server (sshd) in glibc-based Linux systems. This can result in a complete system takeover, malware installation, data manipulation, and the creation of backdoors for persistent access.
Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.
While most government agencies and commercial enterprises have digital services in place, the current volume of usage — including traffic to critical employment, health and retail/eCommerce services — has reached levels that many organizations have never seen before or tested against.
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.
Dynatrace is fully committed to the OpenTelemetry community and to the seamless integration of OpenTelemetry data , including ingestion of custom metrics , into the Dynatrace open analytics platform. Announcing seamless integration of OpenTracing data into Dynatrace PurePath 4.
Cyberattack Cyberattacks involve malicious activities aimed at disrupting services, stealing data, or causing damage. Possible scenarios A Distributed Denial of Service (DDoS) attack overwhelms servers with traffic, making a website or service unavailable.
Managing High Availability (HA) in your PostgreSQL hosting is very important to ensuring your database deployment clusters maintain exceptional uptime and strong operational performance so your data is always available to your application. The primary server is responsible for handling all write operations and maintaining data accuracy.
This section contains the PostgreSQL-specific parameters like authentication, directory paths for data, binary and config, listen ip address etc. All of these tests were performed while the application was running and inserting data to the PostgreSQL database. Standby Server Tests. Reboot the server. Reboot the server.
The key to success is making data in this complex ecosystem actionable, as many types of syslog producers exist. These include traditional on-premises network devices and servers for infrastructure applications like databases, websites, or email. The ultimate challenge lies in making data from syslog-supported log sources actionable.
As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. With agent monitoring, third-party software collects data and reports from the component that’s attached to the agent. Website monitoring.
As a result, it has an advantage over others in terms of visibility, brand image, and driving traffic. Core Web Vitals is a key performance metric that analyzes the website's performance by investigating the data and provides a strategic platform to scale up the website's user experience. What Is Web Performance Testing?
For example, to handle traffic spikes and pay only for what they use. However, serverless applications have unique characteristics that make observability more difficult than in traditional server-based applications. Scale automatically based on the demand and traffic patterns. What are serverless applications?
Security vulnerabilities are weaknesses in applications, operating systems, networks, and other IT services and infrastructure that would allow an attacker to compromise a system, steal data, or otherwise disrupt IT operations. Undetected, the compromised code could allow attackers to access data they’re not authorized to have.
While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. In the Reliability space, our data teams focus on two main approaches.
Cloud migration is the process of transferring some or all your data, software, and operations to a cloud-based computing environment that offers unlimited scale and high availability. With an on-prem data center, the organization bears the burden of securing the physical infrastructure and its digital assets. What is cloud migration?
Would you like to access all your monitoring data on a single platform? Dynatrace has you covered—Dynatrace extensions collect the necessary data and offer improved visibility wherever you need a single platform for IM and APM purposes. Virtual servers. Simplified data analysis presented in topological context.
Such on-premises environments are usually large, typically consisting of thousands of hosts that are organized in physical data centers. As you might know, we recently simplified observability for all custom metrics by making it possible to ingest hundreds of custom data sources into Dynatrace. Events and alerts.
Real-time monitoring with out-of-the-box features Real-time data and monitoring are crucial for maintaining situational awareness of IT environment stability and performance, especially during a crisis. For example, a good course of action is knowing which impacted servers run mission-critical services and remediating those first.
As networks grew and became a critical part of business data circulation, the point of no return was reached: faster connections and more data exchange determined business competitiveness. the data flows). A network packet-level visualization of an application data exchange.
While the first guardian validates the traffic, the second guardian checks the business transactions generated during the observation period. In this case, the four golden signals (latency, traffic, errors, and saturation) are derived from span attributes and DQL metric queries via Dynatrace Grail™.
The Business Insights team at Dynatrace has been working with our largest Digital Experience Monitoring customers to help them turn the Core Web Vitals data they’re collecting with Dynatrace into actionable insights they can use to optimize pages ahead of this June 2021 change in Google’s search ranking algorithm. 28-day lookbacks.
We organize all of the trending information in your field so you don't have to. Join 5,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content