Handling Failure in Long-Running Processes

DZone

In the previous posts in this series, we've seen some examples of long-running processes , how to model them, and where to store the state. So how can we ensure that our long-running process doesn't get into an inconsistent state if something fails along the way?

Batch Processing Large Data Sets With Spring Boot and Spring Batch

DZone

Batch processing of data is an efficient way of processing large volumes of data where data is collected, processed and then batch results are produced. Batch processing can be applied in many use cases. tutorial performance spring boot spring batch batch processing

MezzFS?—?Mounting object storage in Netflix’s media processing platform

The Netflix TechBlog

Mounting object storage in Netflix’s media processing platform By Barak Alon (on behalf of Netflix’s Media Cloud Engineering team) MezzFS (short for “Mezzanine File System”) is a tool we’ve developed at Netflix that mounts cloud objects as local files via FUSE. MezzFS?—?Mounting

Media 276

In-Stream Big Data Processing

Highly Scalable

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.

How DevOps Testing can Enhance the Application Development Process?

Kovair

The post How DevOps Testing can Enhance the Application Development Process? We have entered the digital age where technology is flourishing everywhere and is playing an integral role in our lives. Mobile applications are one great.

Top 9 Free Java Process Monitoring Tools and How to Choose One

DZone

To help equip you for the ongoing process of optimization and the life of debugging ahead of you, we’ve gathered a list of the best tools to monitor the JVM in both development and production environments. java open source performance monitoring jvm process java performance process monitoring

Making Windows Slower Part 2: Process Creation

Randon ASCII

Windows has long had a reputation for slow file operations and slow process creation. This weeks’ blog post covers a technique you can use to make process creation on Windows grow slower over time (with no limit), in a way that will be untraceable for most users!

Monitoring Processes with Percona Monitoring and Management

Percona

A few months ago I wrote a blog post on How to Capture Per Process Metrics in PMM. Since that time, Nick Cabatoff has made a lot of improvements to Process Exporter and I’ve improved the Grafana Dashboard to match. Processes by Disk IO.

Zombie Processes are Eating your Memory

Randon ASCII

Zombies probably won’t consume 32 GB of your memory like they did to me, but zombie processes do exist, and I can help you find them and make sure that developers fix them. He’d even written a tool that would dump a list of zombie processes – their names and counts.

The Digital Twin: A Foundational Concept for Stateful Stream Processing

ScaleOut Software

Traditional stream-processing and complex event processing systems, such as Apache Storm and Software AG’s Apama , have focused on extracting interesting patterns from incoming data with stateless applications.

Process Is No Substitute For Culture

Professor Beekums

I love software process. Process can do wonders for that half. My passion is finding ways to build software faster, but better technology is only half the battle. The other half is a people and organization problem.

How Tricentis’s Robotic Process Automation (RPA) can accelerate the time to value of your software delivery

Tasktop

The time spent on a repetitive configuration process before completing a purchase order can negatively impact your software product’s time to value.

Maximizing Process Performance with Maze, Uber’s Funnel Visualization Platform

Uber Engineering

At Uber’s scale, even a one percent increase in the rate of sign-ups to first trips (the driver conversion rate) carries a … The post Maximizing Process Performance with Maze, Uber’s Funnel Visualization Platform appeared first on Uber Engineering Blog. At Uber, we spend a considerable amount of resources making the driver sign-up experience as easy as possible.

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop

Uber Engineering

With the evolution of storage formats like Apache Parquet and Apache ORC and query engines like Presto and Apache Impala , the Hadoop ecosystem has the potential to become a general-purpose, unified serving layer for workloads that can tolerate latencies … The post Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop appeared first on Uber Engineering Blog.

KeyCDN Launches Image Processing

KeyCDN

We’re thrilled to announce that we’ve added the Image Processing feature! How Does Image Processing Work? The Image Processing feature is available on all Pull Zones. This will improve the image processing performance and decrease the overall cost.

Managing High Availability in PostgreSQL – Part II

Scalegrid

Kill the PostgreSQL process. Manual intervention was required to start the PostgreSQL process again. Stop the PostgreSQL process. Manual intervention was required to start the PostgreSQL process again. Stop the repmgrd process. Kill the PostgreSQL process. Manual intervention was required to start the PostgreSQL process again. Stop the PostgreSQL process and bring it back immediately after health check expiry. Stop the repmgr process.

One SQL to rule them all: an efficient and syntactically idiomatic approach to management of streams and tables

The Morning Paper

In data processing it seems, all roads eventually lead back to SQL! In particular, we need to take care to separate the event time from the processing time (which could be some arbitrary time later). Uncategorized Datastores Stream processing

Back-to-Basics Weekend Reading - Join Processing in Relational.

All Things Distributed

Back-to-Basics Weekend Reading - Join Processing in Relational Databases. In 1992 Priti Mishra and Margaret Eich conducted a survey on what was achieved until then in Join Processing and described in details the algorithms, the implementation complexity and the performance.

MySQL High Availability Framework Explained – Part II: Semisynchronous Replication

Scalegrid

The obvious impact of this is that in the event of a master failure, the slave will not be up-to-date as its SQL thread is still processing the events in the relay log. This will delay the failover process as our framework expects the slave to be fully up-to-date before it can be promoted. To address this issue, we enable multi-threaded slaves with the option slave_parallel_workers to set the number of parallel SQL threads to process events in the relay logs.

European Union Data Protection Authorities Approve Amazon Web Services’ Data Processing Agreement

All Things Distributed

As you all know security, privacy, and protection of our customer’s data is our number one priority and as such we work very closely with regulators to ensure that customers can be assured that they are getting the right protections when processing and storing data in the AWS. The media alert below that went out today gives the details: European Union Data Protection Authorities Approve Amazon Web Services’ Data Processing Agreement.

AWS 62

A Not-Called Function Can Cause a 5X Slowdown

Randon ASCII

Subtitle: Making Windows Slower Part 3: Process Destruction. Process destruction was slow, serialized, and was blocking the system input queue, leading to repeated short mouse-movement hangs when building Chrome. Every Windows process contains several default GDI object handles.

When Your Profiler Lies

Randon ASCII

Last week I wrote about the performance consequences of inadvertently loading gdi32.dll into processes that are created and destroyed at very high rates. This is the first sign of the performance problems that will happen during process destruction. Process destruction (2.3

Object-Oriented Programming Simplifies Digital Twins

ScaleOut Software

These are exciting times in the evolution of stream-processing. As we have seen in previous blogs , the digital twin model offers a breakthrough approach to structuring stateful stream-processing applications. It represents a big step forward for building stream-processing applications.

Step-wise Guide to Perform Penetration Testing

QAMentor

Software Testing Test Process & Best PracticesAny software needs to go through various types of tests to assure that it has the required competitive edge.

European Union Data Protection Authorities Approve Amazon Web Services’ Data Processing Agreement

All Things Distributed

As you all know security, privacy, and protection of our customer’s data is our number one priority and as such we work very closely with regulators to ensure that customers can be assured that they are getting the right protections when processing and storing data in the AWS. The media alert below that went out today gives the details: European Union Data Protection Authorities Approve Amazon Web Services’ Data Processing Agreement.

AWS 40

Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

In previous blogs , we have explored the power of the digital twin model for stateful stream-processing. Digital twins are software abstractions that track the behavior of individual devices in IoT applications. They combine an event handling function with state information about each device.

IoT 56

Improving the User Experience with Uber’s Customer Obsession Ticket Routing Workflow and Orchestration Engine

Uber Engineering

Architecture Open Source Cadence Customer Obsession Platform Customer Support Natural Language Processing NLP Orchestration Engine Ticket Routing Ticket Routing WorkflowEvery day, Uber users around the world initiate customer support tickets through our Customer Obsession Platform.

Building Reliable Reprocessing and Dead Letter Queues with Apache Kafka

Uber Engineering

Architecture 180 Days of Change Avro Batch Processing Configurability Dead Letter Queues Dead-Lettering DLQs Driver Engineering Driver Injury Protection Program Go Insurance Engineering Kafka Microservice Ning Xia Reliability Reliable Reprocessing SLAs Uber Uber EngineeringIn distributed systems, retries are inevitable.

Introducing AthenaX, Uber Engineering’s Open Source Streaming Analytics Platform

Uber Engineering

Architecture Open Source Analytics Analytics Dashboard Apache Calcite Apache Flink Apache Samza Apache Storm App AthenaX Bill Lui Data Data Analytics Event Stream Processing Haohui Mai Kafka Michelangelo Mobile Naveen Cherukuri OS Restaurant Manager SQL Streaming Analytics Structured Query Language Uber Data UberEATS UberPOOL YARNUber facilitates seamless and more enjoyable user experiences by channeling data from a variety of real-time sources.

The Future of Performance Testing

Alex Podelko

While there are still quite a lot of cases where it is still applicable, it needs to evolve into more sophisticated processes tightly integrated with development and other parts of performance engineering. Yes, the tools and process should be easier for non-experts to incorporate some performance testing into continuous development process. But then I recalled that installing LoadRunner was a real process – sometimes taking a half day, with a lot of choices to make.

From bare-metal to Kubernetes

High Scalability

Scaling development processes. This is a guest post by Hugues Alary , Lead Engineer at Betabrand , a retail clothing company and crowdfunding platform, based in San Francisco. This article was originally published here. Early infrastructure. Rackspace. Hardware infrastructure.

Retail 264

Troubleshooting Knative Prometheus GC Issues with Dynatrace

Dynatrace

Keptn is currently leveraging Knative and installs Knative as well as other depending components such as Prometheus during the default keptn installation process. In my case, both prometheus.knative-monitoring pods jumped in Process CPU and I/O request bytes. Dynatrace news.

Faster remainders when the divisor is a constant: beating compilers and libdivide

Daniel Lemire

For this test, I am using an Intel (skylake) processing and GCC 8.1. Not all instructions on modern processors cost the same. Additions and subtractions are cheaper than multiplications which are themselves cheaper than divisions. For this reason, compilers frequently replace division instructions by multiplications. Roughly speaking, it works in this manner. Suppose that you want to divide a variable n by a constant d. You have that n/d = n * (2 N / d ) / (2 N ).

Making Cloud.typography Fast(er)

CSS Wizardry

For me, it was kinda fun to peel back each layer and see how it impacted the next part of the problem, and I hope my detailing it has taught people a thing or two in the process.

OneAgent & ActiveGate release notes, version 1.173

Dynatrace

Improved Oracle process recognition. Previously, all Oracle processes were represented by one Oracle process group and one Oracle process group instance on each host. Starting with OneAgent version 1.173, each Oracle process group will represent a single Oracle SID (unique identifier for every Oracle DB instance). The SID is part of the process group name, and is extracted from process names (Unix) or service description (Windows). Dynatrace news.

Java 120

Extending Dynatrace

Dynatrace

This article we help distinguish between process metrics, external metrics and PurePaths (traces). If you already have the OneAgent installed, and you’d like to bring in additional process metrics into Dynatrace , the OneAgent plugin is a good fit. Dynatrace news.

Parallel programming in Python: mpi4py (part 1)

PDC

print ( 'Hello from process {} out of {}'. In parallel programming with MPI, we need the so-called communicator , which is a group of processes that can talk to each other. To identify the processes with that group, each process is assigned a rank that is unique within the communicator. It also makes sense to know the total number of processes, which is often referred to as the size of the communicator. master process. print ( 'Process {} sent data:'.

Re-Architecting the Video Gatekeeper

The Netflix TechBlog

delivering a large amount of business value in the process. Old Gatekeeper Architecture This model had several problems associated with it: This process was completely I/O bound and put a lot of load on upstream systems. Improved debuggability and visibility into liveness processing.

Deployment challenges with large enterprise systems

Dynatrace

Why Process groups are not perfect. Dynatrace detects automatically identical processes and puts them under the same process group. Dynatrace will create a single process group called backend-API with 2 process instances underneath (host-A and host-B).

A Brief Guide of xPU for AI Accelerators

ACM Sigarch

APU: Accelerated Processing Unit is the AMD’s Fusion architecture that integrates both CPU and GPU on the same die. BPU: Brain Processing Unit is the design of the AI chips by Horizon Robotics. CPU: Central Processing Unit. FPU: Floating Processing Unit (FPU).

How Visual Testing Is Transforming the Way Modern Teams Test Software

DZone

Visual testing is the automated process of detecting and reviewing visual UI changes. The visuals and UI of applications are critical parts of how our users use software, but often teams are still relying on slow, error-prone manual testing processes.

Build automated self-healing systems with xMatters and Dynatrace (Part 1 of 3)

Dynatrace

In this three-part blog series, we’ll share the following three common problem scenarios that you can easily solve by building an automated self-healing system with Dynatrace and xMatters Flow Designer: Process crash. As a first use case, let’s explore how your DevOps teams can prevent a process crash from taking down services across an organization—in five easy steps. Use case #1: Prevent a process crash from taking down services across an organization. Dynatrace news.

Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Its goal is to assign running processes to time slices of the CPU in a “fair” way. In this way a user-space process defines a “fence” within which CFS operates for each container. This user-space process is a Titus subsystem called titus-isolate which works as follows.

Cache 275