Scalegrid

JANUARY 8, 2024

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Using AI for Enhanced Cloud Operations The integration of AI in cloud computing is enhancing operational efficiency in several ways.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Scalegrid

FEBRUARY 8, 2024

Their design emphasizes increasing availability by spreading out files among different nodes or servers — this approach significantly reduces risks associated with losing or corrupting data due to node failure. This process effectively duplicates essential parts of information to safeguard against potential loss.

Storage 130

Storage Systems Big Data Azure 130

The Netflix TechBlog

NOVEMBER 17, 2022

A distinct, NN-based, video processing block can evolve independently, be used beyond video downscaling and be combined with different codecs. While conventional video codecs remain prevalent, NN-based video encoding tools are flourishing and closing the performance gap in terms of compression efficiency.

Network 292

Network Media Innovation Efficiency 292

The Netflix TechBlog

MARCH 7, 2024

Since its inception , Metaflow has been designed to provide a human-friendly API for building data and ML (and today AI) applications and deploying them in our production infrastructure frictionlessly. In other cases, it is more convenient to share the results via a low-latency API.

Systems 226

Systems Media Cache Open Source 226

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. A typical design pattern is the use of a semantic search over a domain-specific knowledge base, like internal documentation, to provide the required context in the prompt.

Monitoring 161

Monitoring Latency Metrics Azure 161

The Netflix TechBlog

MARCH 4, 2024

We have deployed Auto Remediation in production for handling memory configuration errors and unclassified errors of Spark jobs and observed its efficiency and effectiveness (e.g., For efficient error handling, Netflix developed an error classification service, called Pensive, which leverages a rule-based classifier for error classification.

Tuning 210

Tuning Efficiency Big Data Engineering 210

Dynatrace

JULY 24, 2023

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. This evolution in automation, referred to as answer-driven automation, empowers teams to address complex issues in real time, optimize workflows, and enhance overall operational efficiency.

DevOps 216

DevOps Traffic Efficiency Servers 216

Scalegrid

JANUARY 12, 2024

This article analyzes cloud workloads, delving into their forms, functions, and how they influence the cost and efficiency of your cloud infrastructure. In the realm of cloud-based business operations, there is an increasing dependence on complex information processing patterns.

Cloud 130

Cloud Virtualization Storage Efficiency 130

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. Massively parallel processing. What is a data lakehouse? Data warehouses.

Artificial Intelligence 205

Artificial Intelligence Analytics Storage Government 205

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. The public cloud’s ability to scale efficiently enables ‘cloudbursting’ when demand spikes without requiring businesses to overprovision their own infrastructures.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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

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. Fault-tolerance.

Big Data 154

Big Data Processing Lambda Database 154

Percona

APRIL 17, 2023

The CFQ works well for many general use cases but lacks latency guarantees. The deadline excels at latency-sensitive use cases ( like databases ), and noop is closer to no schedule at all. 25.84 - Total 21.04 zone_reclaim_mode In some OS versions, the vm.zone_reclaim_mode is enabled. 25.84 - Total 21.04

Best Practices 52

Best Practices Design Tuning Database 52

Dynatrace

APRIL 5, 2021

The 2014 launch of AWS Lambda marked a milestone in how organizations use cloud services to deliver their applications more efficiently, by running functions at the edge of the cloud without the cost and operational overhead of on-premises servers. Real-time file processing, for quickly indexing files, processing logs, and validating content.

Lambda 177

Lambda AWS Serverless Hardware 177

Dynatrace

DECEMBER 15, 2022

This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. So, what is ITOps? How does ITOps create business value?

Artificial Intelligence 198

Artificial Intelligence DevOps Hardware Virtualization 198

Dynatrace

FEBRUARY 24, 2021

DevOps is focused on optimizing software development and delivery, and SRE is focused on operations processes. DevOps is not a specific process, but rather a general collection of flexible software creation and delivery practices that looks to close the gap between software development and IT operations. Reduced latency.

DevOps 186

DevOps Software Engineering Speed Google 186

Dynatrace

JANUARY 18, 2023

However, getting reliable answers from observability data so teams can automate more processes to ensure speed, quality, and reliability can be challenging. SRE applies software engineering principles to operations and infrastructure processes. Indeed, the pressure to digitally transform is increasing. What is DevOps?

DevOps 194

DevOps Best Practices Innovation Strategy 194

The Netflix TechBlog

JUNE 4, 2019

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. Its goal is to assign running processes to time slices of the CPU in a “fair” way. So why mess with it?

Cache 251

Cache Latency Airlines Logistics 251

Percona

MARCH 29, 2023

As the amount of data grows, the need for efficient data compression becomes increasingly important to save storage space, reduce I/O overhead, and improve query performance. Snappy compression is designed to be fast and efficient regarding memory usage, making it a good fit for MongoDB workloads.

Storage 107

Storage Network Open Source Latency 107

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 192

DevOps Metrics Best Practices Latency 192

The Netflix TechBlog

SEPTEMBER 8, 2020

For each route we migrated, we wanted to make sure we were not introducing any regressions: either in the form of missing (or worse, wrong) data, or by increasing the latency of each endpoint. Being able to canary a new route let us verify latency and error rates were within acceptable limits. This meant that data that was static (e.g.

Latency 233

Latency Cache Java Traffic 233

The Netflix TechBlog

OCTOBER 19, 2020

Now let’s look at how we designed the tracing infrastructure that powers Edgar. 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.

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

The Morning Paper

NOVEMBER 10, 2019

It’s been clear for a while that software designed explicitly for the data center environment will increasingly want/need to make different design trade-offs to e.g. general-purpose systems software that you might install on your own machines. The desire for CPU efficiency and lower latencies is easy to understand.

Network 92

Network Transportation Latency Entertainment 92

Dynatrace

OCTOBER 1, 2021

The goal of observability is to understand what’s happening across all these environments and among the technologies, so you can detect and resolve issues to keep your systems efficient and reliable and your customers happy. The architects and developers who create the software must design it to be observed.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

The Morning Paper

NOVEMBER 15, 2020

Improving the efficiency with which we can coordinate work across a collection of units (see the Universal Scalability Law ). With more nodes and more coordination comes more complexity, both in design and operation. This makes the whole system latency sensitive. Increasing the amount of work we can do on a single unit.

Servers 128

Servers Hardware Latency Design 128

Dynatrace

JANUARY 13, 2022

Real user monitoring (RUM) is a performance monitoring process that collects detailed data about a user’s interaction with an application. Analyzing a clinician’s clickstream when using an electronic medical record system to better improve the efficiency of data entry. What is real user monitoring?

Monitoring 176

Monitoring Latency Mobile Best Practices 176

Brendan Gregg

FEBRUARY 28, 2023

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP

Performance 110

Performance Latency Cache Virtualization 110

Adrian Cockcroft

JANUARY 20, 2023

Here’s some predictions I’m making: Jack Dongarra’s efforts to highlight the low efficiency of the HPCG benchmark as an issue will influence the next generation of supercomputer architectures to optimize for sparse matrix computations. Jack Dongarra talked about the scores, and pointed out the low efficiency on some important workloads.

Architecture 52

Architecture Latency Benchmarking AWS 52

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20. Emphasis mine ). Emphasis mine ).

Cloud 104

Cloud Big Data Latency Architecture 104

The Morning Paper

FEBRUARY 6, 2020

’ Stateless is fine until you need state, at which point the coarse-grained solutions offered by current platforms limit the kinds of application designs that work well. On the Cloudburst design teams’ wish list: A running function’s ‘hot’ data should be kept physically nearby for low-latency access.

Lambda 98

Lambda Serverless Cache Latency 98

The Morning Paper

OCTOBER 11, 2020

That’s not enough bandwidth to download data from thousands of nano-satellites, nor enough to efficiently reconfigure a cluster via the uplink. Orbital Edge Computing (OEC) is designed to do just that. Formation flying, and formation processing. This would take just 30s at 200 Mbit/s. Computing on the edge with cote.

Systems 125

Systems Latency Architecture Energy 125

The Morning Paper

JANUARY 30, 2020

Edge servers are the middle ground – more compute power than a mobile device, but with latency of just a few ms. The current system assumes an application specific regression model is available on the servers which can predict processing time given the current parameters of the job (e.g.

Mobile 104

Mobile Cloud Latency Games 104

Dynatrace

SEPTEMBER 30, 2021

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. A key step in digital transformation is migrating from traditional on-prem IT processes to adopting cloud services. What is cloud migration?

Cloud 162

Cloud Traffic Best Practices Strategy 162

The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Processing 210

Processing Big Data Efficiency Engineering 210

The Morning Paper

JANUARY 28, 2020

Shredder is " a low-latency multi-tenant cloud store that allows small units of computation to be performed directly within storage nodes. " From an operator perspective it makes it harder to follow the classic cloud-native design in which a global storage layer is separate to compute. Shredder in action.

Serverless 99

Serverless Storage Latency Cloud 99

Dynatrace

APRIL 26, 2022

Digital experience monitoring enables companies to respond to issues more efficiently in real time, and, through enrichment with the right business data, understand how end-user experience of their digital products significantly affects business key performance indicators (KPIs). What DEM and business observability mean for the bottom line.

Monitoring 199

Monitoring Social Media IoT Metrics 199

The Netflix TechBlog

JANUARY 10, 2024

Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. The Netflix video processing pipeline went live with the launch of our streaming service in 2007. The Netflix video processing pipeline went live with the launch of our streaming service in 2007.

Processing 229

Processing Media Latency Innovation 229