Scalegrid

JANUARY 19, 2024

When a MongoDB rollback happens, it can cause trouble to your data integrity and system consistency. Understanding how to address a rollback is critical for minimizing potential data loss and maintaining seamless operations. With direct, actionable insights, prepare to navigate the complexities of rollbacks with confidence.

Database 130

Database Network Servers Monitoring 130

Dynatrace

DECEMBER 27, 2022

By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. When organizations implement SLOs, they can improve software development processes and application performance. This telemetry data serves as the basis for establishing meaningful SLOs. Reliability.

Software 256

Software Software Benchmarking Latency 256

The Netflix TechBlog

MAY 4, 2023

It can happen on an edge API system servicing customer devices, between the edge and mid-tier services, or from mid-tiers to data stores. It provides a good read on the availability and latency ranges under different production conditions. Replay Solution The replay traffic testing solution comprises two essential components.

Traffic 339

Traffic Latency Tuning Systems 339

DZone

JUNE 15, 2023

In order to gain insight into these problems, we gather a range of metrics and logs to monitor the utilization of system resources such as CPU, memory, and application-specific latencies. It is worth noting that this data collection process does not impact the performance of the application.

Latency 246

Latency Storage Strategy Metrics 246

Dynatrace

MAY 31, 2023

As a result, site reliability has emerged as a critical success metric for many organizations. Maintaining reliable uptime and consistent service quality has become more complex as organizations expand their computing footprints across multiple data centers and in the cloud. More than one in seven outages cost more than $1 million.

Best Practices 216

Best Practices DevOps Latency Metrics 216

Dynatrace

MARCH 16, 2023

Enterprises now have access to myriad metrics they can track and measure, but an abundance of choice doesn’t equal actionable insight. Indeed, 54% of SREs say they handle too many metrics, making it increasingly difficult to find the most relevant ones for a particular service, according to the Dynatrace State of SRE Report.

DevOps 207

DevOps Latency Metrics Traffic 207

Dynatrace

JANUARY 31, 2024

This blog post explores how AI observability enables organizations to predict and control costs, performance, and data reliability. It also shows how data observability relates to business outcomes as organizations embrace generative AI. GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues.

Cache 199

Cache Azure Infrastructure Monitoring 199

Dynatrace

MARCH 29, 2024

Providing at-a-glance data makes it possible for teams to quickly identify high-level issues and then drill down into the details. ” The Dynatrace Kubernetes app also provides process ownership data, ensuring information is directed to the right team and root causes are addressed. ” Data supports those declarations.

Engineering 218

Engineering DevOps Operating System Open Source 218

Dynatrace

APRIL 7, 2023

Customers can use AWS Lambda Response Streaming to improve performance for latency-sensitive applications and return larger payload sizes. Lambda functions allow teams to run code for applications, back-end services, streaming processing, or any layer of the stack with less overhead. Return larger payload sizes.

Lambda 208

Lambda AWS Serverless Latency 208

The Netflix TechBlog

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226

Systems Media Cache Open Source 226

Dynatrace

APRIL 8, 2024

Optimize the IT infrastructure supporting risk management processes and controls for maximum performance and resilience. The IT infrastructure, services, and applications that enable processes for risk management must perform optimally. Deploy risk-based estimates and models with confidence, accuracy, transparency, and speed.

Analytics 193

Analytics Infrastructure Efficiency Technology 193

Dynatrace

SEPTEMBER 13, 2023

These workflows also utilize Davis® , the Dynatrace causal AI engine, and all your observability and security data across all platforms, in context, at scale, and in real-time. This process enables you to continuously evaluate software against predefined quality criteria and service level objectives (SLOs) in pre-production environments.

AWS 240

AWS Efficiency Azure Cloud 240

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Modularity and flexibility.

Big Data 154

Big Data Processing Lambda Database 154

Dynatrace

JUNE 7, 2023

Advanced AI applications using OpenAI services don’t just forward user input to OpenAI models; they also require client-side pre- and post-processing. It shows critical SLOs for latency and availability, as well as the most important OpenAI generative AI service metrics, such as response time, error count, and the overall number of requests.

Monitoring 159

Monitoring Latency Metrics Azure 159

Dynatrace

NOVEMBER 6, 2023

Cloud complexity and data proliferation are two of the most significant challenges that IT teams are facing today. Computing environments are scaling to new heights, resulting in more data that makes pinpointing root causes and vulnerabilities even more challenging. But not all teams use the same observability data in the same way.

Development 255

Development DevOps Programming Cloud 255

Dynatrace

APRIL 25, 2023

Higher latency and cold start issues due to the initialization time of the functions. Observability is typically achieved by collecting three types of data from a system, metrics, logs and traces. Collecting these data types from serverless applications is not straightforward due to their ephemeral nature.

Serverless 200

Serverless Lambda Azure AWS 200

Dynatrace

MAY 19, 2022

However, many teams struggle with knowing which ones to use and how to incorporate them into the processes. Below, several Dynatrace customers shared their SLO management journey and discussed the resulting dashboards they rely on daily to manage their mission-critical business processes and applications. What are SLOs?

Automotive 263

Automotive Latency Architecture Azure 263

Dynatrace

MAY 17, 2023

To ensure high standards, it’s essential that your organization establish automated validations in an early phase of the software development process—ideally when code is written. In this case, the four golden signals (latency, traffic, errors, and saturation) are derived from span attributes and DQL metric queries via Dynatrace Grail™.

DevOps 180

DevOps Traffic Latency Best Practices 180

Dynatrace

APRIL 5, 2021

AWS Lambda is a serverless compute service that can run code in response to predetermined events or conditions and automatically manage all the computing resources required for those processes. Real-time file processing, for quickly indexing files, processing logs, and validating content. Data entering a stream.

Lambda 175

Lambda AWS Serverless Hardware 175

The Netflix TechBlog

SEPTEMBER 8, 2020

This allowed Android engineers to have much more control and observability over how we get our data. Background The Netflix Android app uses the falcor data model and query protocol. For example, the artwork service is separate from the video metadata service, but we need the data from both in the detail key.

Latency 233

Latency Cache Java Traffic 233

The Netflix TechBlog

AUGUST 30, 2021

The challenge, then, is to be able to ingest and process these events in a scalable manner, i.e., scaling with the number of devices, which will be the focus of this blog post. These checkpoint events enable faster state reconstruction by consumers of the data feed while guarding against missed updates.

Latency 213

Latency Traffic Transportation Hardware 213

Dynatrace

DECEMBER 15, 2022

Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. So, what is ITOps? What is ITOps?

Artificial Intelligence 195

Artificial Intelligence DevOps Hardware Virtualization 195

Dynatrace

JUNE 8, 2020

Dynatrace Mission Control collects the health monitoring observability metrics for both our Dynatrace SaaS as well as Dynatrace Managed customers. Dynatrace Managed operates as a SaaS solution that keeps your data and data analysis on-premise in your own data center, thereby fulfilling the highest privacy and regulatory needs.

Software 164

Software Software Programming Metrics 164

Dynatrace

APRIL 26, 2022

Fast, consistent application delivery creates a positive user experience that can ultimately drive customer loyalty and improve business metrics like conversion rate and user retention. DEM can give organizations business observability—insight into the effects of user experience on the bottom line. What is digital experience monitoring?

Monitoring 196

Monitoring Social Media IoT Metrics 196

Dynatrace

FEBRUARY 2, 2022

service availability with <50ms latency for an application with no revenue impact. A broken SLO with no owner can take longer to remediate and is more likely to recur compared to an SLO with an owner and a well-defined remediation process. To avoid this, start the SLO discussion early in the design process.

DevOps 189

DevOps Metrics Best Practices Latency 189

Dynatrace

DECEMBER 2, 2021

And why have SLOs and SLIs become so important as teams automate processes to consistently meet SLAs and error budgets? As defined by Gartner , service-level objectives are an agreed-upon target within an SLA that must be achieved for each activity, function, and process to provide the best opportunity for customer success.

Metrics 184

Metrics Best Practices DevOps Infrastructure 184

Speed Curve

FEBRUARY 5, 2024

However, that pesky 20% on the back end can have a big impact on downstream metrics like First Contentful Paint (FCP), Largest Contentful Paint (LCP), and any other 'loading' metric you can think of. SpeedCurve's RUM collection library – lux.js – accesses this interface to collect custom data from the user agent.

Servers 57

Servers Cache Retail Benchmarking 57

Dynatrace

MAY 5, 2021

As more organizations respond to the pressure to release better software faster, there is an increasing need to build quality gates into every stage of BizDevOps processes , from early development to deployment. Automating quality gates creates reliable checks and balances and speeds up the process by avoiding manual intervention.

Benchmarking 176

Benchmarking Latency Speed Software 176

The Netflix TechBlog

OCTOBER 19, 2020

Reconstructing a streaming session was a tedious and time consuming process that involved tracing all interactions (requests) between the Netflix app, our Content Delivery Network (CDN), and backend microservices. The process started with manual pull of member account information that was part of the session.

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

Scalegrid

MARCH 22, 2024

Crafting Your Multi-Cloud Blueprint Formulating a comprehensive multi-cloud framework is an intricate process that requires a business’s specific requirements, choosing suitable cloud services, and optimizing for performance and affordability. They can also bolster uptime and limit latency issues or potential downtimes.

Strategy 130

Strategy Cloud Government Innovation 130

Adrian Cockcroft

JANUARY 29, 2023

The mean and percentile measurements hide this structure, but the rest of this post will show how the structure can be measured and analyzed so that you can figure out a useful model of your system, understand what is driving the long tail of latencies and come up with better SLAs and measures of capacity.

Lambda 98

Lambda Latency Cache C++ 98

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. Database-service views provide all the metrics you need to set up high-performance database services. See the health of your big data resources at a glance.

Azure 145

Azure Cloud Big Data Virtualization 145

Percona

JUNE 22, 2023

Database uptime and availability Monitoring database uptime and availability is crucial as it directly impacts the availability of critical data and the performance of applications or websites that rely on the MySQL database. Disk space usage Monitor the disk space usage of MySQL data files, log files, and temporary files.

Performance 105

Performance Monitoring Traffic Database 105

The Morning Paper

OCTOBER 6, 2019

Prediction serving latency matters. And by the way, wouldn’t it be wonderful to see data confirming or denying that hypothesis in future reports!). Booking.com estimate the value delivered by a model through randomized controlled trials which measure the impact on business metrics. Get early feedback on model quality.

Latency 102

Latency Metrics Cache Design 102

Speed Curve

DECEMBER 4, 2023

Earlier this year, when Google announced that Interaction to Next Paint (INP) will replace First Input Delay (FID) as the responsiveness metric in Core Web Vitals in *gulp* March of 2024, we had a lot to say about it. TLDR: FID doesn't correlate with real user behavior, so we don't endorse it as a meaningful metric.) for mobile.

Mobile 54

Mobile Performance Metrics Google 54

Alex Russell

FEBRUARY 28, 2022

The metrics that we report against implicitly cleave these into different "camps", leaving us thinking about pre- and post-load as distinct universes. Input is received and processed. The chief effect of the architectural difference is to shift the distribution of latency within the loop. But what if they aren't?

Performance 104

Performance Latency Architecture Network 104

The Netflix TechBlog

JULY 26, 2021

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.

Big Data 253

Big Data Government Analytics Processing 253