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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.
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. This approach has a handful of benefits.
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.
Digital transformation strategies are fundamentally changing how organizations operate and deliver value to customers. A comprehensive digital transformation strategy can help organizations better understand the market, reach customers more effectively, and respond to changing demand more quickly. Competitive advantage.
Although this indexing strategy worked smoothly for a while, interesting challenges started coming up and we started to notice performance issues over time. It was time to take a step back and reevaluate our ES data indexing and sharding strategy. We also changed our mapping strategy to overcome these issues.
The three strategies we will discuss today are AB Testing , Replay Testing, and Sticky Canaries. Let’s discuss the three testing strategies in further detail. The control group’s traffic utilized the legacy Falcor stack, while the experiment population leveraged the new GraphQL client and was directed to the GraphQL Shim.
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.
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. There are proven strategies for handling this.
In this article, we’ll dive deep into the concept of database sharding, a critical technique for scaling databases to handle large volumes of data and high levels of traffic. This section will provide insights into the architecture and strategies to ensure efficient query processing in a sharded environment.
Even when the staging environment closely mirrors the production environment, achieving a complete replication of all potential scenarios, such as simulating extremely high traffic volumes to assess software performance, remains challenging. This can lead to a lack of insight into how the code will behave when exposed to heavy traffic.
It’s also critical to have a strategy in place to address these outages, including both documented remediation processes and an observability platform to help you proactively identify and resolve issues to minimize customer and business impact. Outages can disrupt services, cause financial losses, and damage brand reputations.
To address potentially high numbers of requests during online shopping events like Singles Day or Black Friday, it’s crucial that this online shop have a memory storage strategy that allows for speed, scaling, and resilience of all microservices, especially the shopping cart service.
But what happens when traffic bursts overwhelm your system? In this post, we'll explore both strategies through a simple simulation in Colab, allowing you to see the impact of changing parameters on system performance. Queueing requests is a common solution, but what's the best approach: FIFO or LIFO?
A cloud migration strategy, however, provides technical optimization that’s also firmly rooted in the business value chain. Migrating to the cloud is a strategy many organizations pursue to streamline and consolidate their security efforts. Likewise, you can scale down when your application experiences decreased traffic.
API resilience is about creating systems that can recover gracefully from disruptions, such as network outages or sudden traffic spikes, ensuring they remain reliable and secure. In this article, Ill share practical strategies for designing APIs that scale, handle errors effectively, and remain secure over time.
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.
Confused about multi-cloud vs hybrid cloud and which is the right strategy for your organization? Real-world examples like Spotify’s multi-cloud strategy for cost reduction and performance, and Netflix’s hybrid cloud setup for efficient content streaming and creation, illustrate the practical applications of each model.
Network traffic growth is the main reason for increasing spending, largely because of the adoption of hybrid and multi-cloud architectures. Unifying data, unifying observability Merging siloed data streams in a unified observ ability strategy requires a different approach.
Website monitoring examines a cloud-hosted website’s processes, traffic, availability, and resource use. An effective IT infrastructure monitoring strategy includes the following best practices: Determine the best cloud tooling and services for your specific cloud environment. Website monitoring. Cloud-server monitoring.
Part 3: System Strategies and Architecture By: VarunKhaitan With special thanks to my stunning colleagues: Mallika Rao , Esmir Mesic , HugoMarques This blog post is a continuation of Part 2 , where we cleared the ambiguity around title launch observability at Netflix. We call this capability TimeTravel.
For example, if you’re monitoring network traffic and the average over the past 7 days is 500 Mbps, the threshold will adapt to this baseline. An anomaly will be identified if traffic suddenly drops below 200 Mbps or above 800 Mbps, helping you identify unusual spikes or drops.
When the SLO status converges to an optimal value of 100%, and there’s substantial traffic (calls/min), BurnRate becomes more relevant for anomaly detection. SLOs must be evaluated at 100%, even when there is currently no traffic. What characterizes a weak SLO? Use the default transformation.
To ensure the safety of their customers, employees, and business data, organizations must have a strategy to protect against zero-day vulnerabilities. Typically, organizations might experience abnormal scanning activity or an unexpected traffic influx that is coming from one specific client. What is a zero-day vulnerability?
At Dynatrace, we’re constantly striving to come up with solutions that can help modernize your performance and user experience monitoring strategies. Cost and traffic control. The following settings can be applied: Cost and traffic control : 100%. The following settings can be applied: Cost and traffic control : 25%.
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. Think of it as a sophisticated traffic management system that ensures smooth flow and prevents congestion.
This means that Dynatrace alerts more quickly when an error spike occurs in a high-traffic service (compared to a low-traffic service where statistical confidence is lower). This setting distinguishes between slowdown alerts and error detection, so that you can choose an individual strategy for each.
Therefore, the team integrated the Dynatrace observability platform into numerous aspects of its software development process to ensure the new code could meet their standards and be performant during the pandemic—when the application saw its highest traffic on record.
Observability becomes mandatory for any serious sustainability strategy in IT. During the holiday season, an e-commerce platform anticipating a traffic surge could use preventive observability to predict slowdowns or overloads, proactively scale resources, optimize performance, and balance cloud costs.
To detect issues proactively, we need to simulate traffic and predict system behavior in advance. Once artificial traffic is generated, discarding the response object and relying solely on logs becomes inefficient.
Implementing a robust monitoring and observability strategy has become the foundation of an organization’s ability to improve business resiliency and stay in control of their critical IT environments. Each of these factors can present unique challenges individually or in combination.
Here are some other examples of collaboration with business stakeholders: Unexpected traffic surge in the data center or A Dynatrace Champions guide to get ahead of digital marketing campaign. Extend and automate your SRE strategy to Business Level Objective Monitoring.
The good news: even for latecomers to the compliance party, compliance is perfectly doable within the timeframe given the right tools and strategies. Observability provides banks and other financial institutions with real-time insight into their IT environment, including applications, infrastructure, and network traffic.
This enables proactive changes such as resource autoscaling, traffic shifting, or preventative rollbacks of bad code deployment ahead of time. One study found that 93% of companies have a multicloud strategy to enable them to use the best qualities of each cloud provider for different situations.
264/AVC Main profile family still represents a substantial portion of the members viewing hours and an even larger portion of the traffic. It is important to highlight that the expected >20% reduction in average session bitrate for these encodes corresponds to a significant reduction in the overall Netflix traffic as well.
Streamline development and delivery processes Nowadays, digital transformation strategies are executed by almost every organization across all industries. Dynatrace users can now unlock answer-driven automation to safely and securely release new features to customers while ensuring production SLOs are intact.
In the event of an isolated failure we first pre-scale microservices in the healthy regions after which we can shift traffic away from the failing one. In 2013 we first developed our multi-regional availability strategy in response to a catalyst that led us to re-architect the way our service operates.
Organizations that have transitioned to agile software development strategies (including the adoption of a DevOps culture and continuous delivery automation) enforce automated solutions for such decision making—or at the very least, use automation in the gathering of a release-quality metrics. How Release Analysis works. Kubernetes metadata.
Handling Bursty Traffic : Managing significant traffic spikes during high-demand events, such as new content launches or regional failovers. Sharded Infrastructure : Leveraging the Data Gateway Platform , we can deploy single-tenant and/or multi-tenant infrastructure with the necessary access and traffic isolation.
Resource consumption & traffic analysis. If you want to read up on migration strategies check out my blog on 6-R Migration Strategies. What is the network traffic going to be between services we migrate and those that have to stay in the current data center? Step 3: Detailed Traffic Dependency Analysis.
In this post, we compare ScaleGrid’s Bring Your Own Cloud (BYOC) plan vs. the standard Dedicated Hosting model to help you determine the best strategy for your MySQL, PostgreSQL, Redis™ and MongoDB® database deployment. This can result in significant cost savings for high traffic applications. SSH Access to Machine.
That’s why traceability, scalability, and reliability are crucial aspects of a cloud strategy, and for this county, OpenShift and Dynatrace delivered on these needs. Dynatrace’s AI engine, Davis automatically identified high traffic surges on the county website as the fire took hold. High Traffic Notification.
Existing data got updated to be backward compatible without impacting the existing running production traffic. Data Sharding strategy in elasticsearch is updated to provide low search latency (as described in blog post) Design of new Cassandra reverse indices to support different sets of queries.
This is because each of these traffic vectors comes with unique challenges. The following are three strategies worth considering. Synthetic testing as part of a unified observability strategy To make synthetic testing easy to develop and maintain, it should be part of a wider observability strategy.
RUM, however, has some limitations, including the following: RUM requires traffic to be useful. Because RUM relies on user-generated traffic, it’s hard to indicate persistent issues across the board. Real user monitoring limitations. RUM is ideally suited to provide real metrics from real users navigating a site or application.
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