- Discuss the role of Observability (Logging; Tracing; and Metric) in modern architecture.
- How to implement observability in Golang using OpenCensus.
- The 4 golden signals when designing the metrics.
- How to apply observability into the process.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk gives an overview of the OpenTelemetry project and then outlines some production-proven architectures for improving the observability of your applications and systems.
With Instana the "Classic" Observability is not the end of the line. Find out what Observability means and how it can help DevOps, Developers, SREs day-by-day.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk gives an overview of the OpenTelemetry project and then outlines some production-proven architectures for improving the observability of your applications and systems.
With Instana the "Classic" Observability is not the end of the line. Find out what Observability means and how it can help DevOps, Developers, SREs day-by-day.
Everyone wants observability into their system, but find themselves with too many vendors and tools, each with its own API, SDK, agent and collectors.
In this talk I will present OpenTelemetry, an ambitious open source project with the promise of a unified framework for collecting observability data. With OpenTelemetry you could instrument your application in a vendor-agnostic way, and then analyze the telemetry data in your backend tool of choice, whether Prometheus, Jaeger, Zipkin, or others.
I will cover the current state of the various projects of OpenTelemetry (across programming languages, exporters, receivers, protocols), some of which not even GA yet, and provide useful guidance on how to get started with it.
What is observability and how is it different from traditional monitoring? How do we effectively monitor and debug complex, elastic microservice architectures? In this interactive discussion, we’ll answer these questions. We’ll also introduce the idea of an “observability pipeline” as a way to empower teams following DevOps practices. Lastly, we’ll demo cloud-native observability tools that fit this “observability pipeline” model, including Fluentd, OpenTracing, and Jaeger.
Observability has emerged as one of the hottest topics on the DevOps landscape. Organizations seek to improve visibility into their cloud infrastructure and applications and identify production issues that may negatively impact #customerexperience.
➡️ But what are some of the best practices for scaling observability for modernapplications?
➡️ What challenges are #cloudplatforms facing?
Explore how to overcome the challenges and unlock speed, observability, and automation across your DevOps lifecycle.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk covers the fundamental concepts of observability and then demonstrates how to instrument your applications using the OpenTelemetry libraries.
More Than Monitoring: How Observability Takes You From Firefighting to Fire P...DevOps.com
For some, observability is just a hollow rebranding of monitoring, for others it’s monitoring on steroids. But what if we told you observability is the new way to find out why—not just if—your distributed system or application isn’t working as expected? Today, we see that traditional monitoring approaches can fall short if a system or application doesn’t adequately externalize its state.
This is truer as workloads move into the cloud and leverage ephemeral technologies, such as microservices and containers. To reach observability, IT and DevOps teams need to correlate different sources from logs, metrics, traces, events and more. This becomes even more challenging when defining the online revenue impact of a failed container—after all, this is what really matters to the business.
This webinar will cover:
The differences between observability and monitoring
Why it is a bigger challenge in a multicloud and containerized world
How observability results in less firefighting and more fire prevention
How new platforms can help gain observability (on premises and in the cloud) for containers, microservices and even SAP or mainframes
Is your company built on software? How do you know if your customer's experience is slow and sucks? How do you debug slowness or troubleshoot an incident? Observability! David Mitchell, VP of Engineering at Datadog will talk to use about Observability, why it's important, what it is and how Datadog helps reduce toil in your environment.
GDG Cloud Southlake #13
The pervasiveness of cloud and containers has led to systems that are much more distributed and dynamic in nature. Highly elastic microservice and serverless architectures mean containers spin up on demand and scale to zero when that demand goes away. In this world, servers are very much cattle, not pets. This shift has exposed deficiencies in some of the tools and practices we used in the world of servers-as-pets. Specifically, there are questions around how we monitor and debug these types of systems at scale. And with the rise of DevOps and product mindset, making data-driven decisions is becoming increasingly important for agile development teams.
In this talk, we discuss a new approach to system monitoring and data collection: the observability pipeline. For organizations that are heavily siloed, this approach can help empower teams when it comes to operating their software. The observability pipeline provides a layer of abstraction that allows you to get operational data such as logs and metrics everywhere it needs to be without impacting developers and the core system. Unlocking this data can also be a huge win for the business with things like auditability, business analytics, and pricing. Lastly, it allows you to change backing data systems easily or test multiple in parallel. With the amount of data and the number of tools modern systems demand these days, we'll see how the observability pipeline becomes just as essential to the operations of a service as the CI/CD pipeline.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk covers the latest concepts in observability and then demonstrates how to configure and deploy various OpenTelemetry components to effectively meet your SLO's.
My contribution to the "Grafana & Friends" Meetup.
This presentation goes into the context in the Observability landscape, the basics of OpenTelemetry with its signals and lookout what to expect next.
Whether you’re an enterprise migrating to cloud native or born in the cloud, most of today’s APM and Observability tools don’t support how your engineers and DevOps teams need to develop, deploy, and support their software. Observability needs to shift left and reflect the modern way companies organize their development teams and their vital interdependencies.
Chronosphere is the only vendor addressing the unique requirements for observability in a cloud native world. Join this webinar to learn:
- What cloud native observability is and how it is different from the promises made by traditional cloud APM and observability vendors
- How to use cloud native observability to do more “Dev” and less “Ops” so you can dramatically improve developer and engineer workflows and productivity
- How to make on-call shifts less stressful so your engineers aren’t getting burned out
Modern cloud-native applications are incredibly complex systems. Keeping the systems healthy and meeting SLAs for our customers is crucial for long-term success. In this session, we will dive into the three pillars of observability - metrics, logs, tracing - the foundation of successful troubleshooting in distributed systems. You'll learn the gotchas and pitfalls of rolling out the OpenTelemetry stack on Kubernetes to effectively collect all your signals without worrying about a vendor lock in. Additionally we will replace parts of the Prometheus stack to scrape metrics with OpenTelemetry collector and operator.
This presentation gives audiences a broad viewpoint from old to modern architecture. How Kubernetes and service mesh (istio) can help developers in those missions:
- Explain from traditional to modern architecture. The role of Kubernetes in modern architecture.
- Build basic k8s components from the ground up with illustrations: Pod; Node; Service; ReplicaSet; Deployment; Namespace; Ingress ...
- Kubernetes under the developer viewpoint: write a YAML application file and deploy k8s application to the cluster.
- Kubernetes advanced concepts: master node design, how does the auto-scale for pods/nodes work, Kubernetes networking model.
- Discuss microservice challenges. The role of the service mesh in the microservice ecosystem.
- Introduce Envoy, istio and their application in the service mesh.
Everything You wanted to Know About Distributed TracingAmuhinda Hungai
In the age of microservices, understanding how applications are executing in a highly distributed environment can be complicated. Looking at log files only gives a snapshot of the whole story and looking at a single service in isolation simply does not give enough information. Each service is just one side of a bigger story. Distributed tracing has emerged as an invaluable technique that succeeds in summarizing all sides of the story into a shared timeline. Yet deploying it can be quite challenging, especially in the large scale, polyglot environments of modern companies that mix together many different technologies. During this session, we will take a look at patterns and means to implement Tracing for services. After introducing the basic concepts we will cover how the tracing model works, and how to safely use it in production to troubleshoot and diagnose issues.
This talk is about monitoring with Prometheus. A progression is shown from monitoring concept, to Micrometer, Prometheus and Grafana.
Presented at Alithya by Richard Langlois and Gervais Naoussi, on September 19th, 2018
Webinar Monitoring in era of cloud computingCREATE-NET
The webinar "Monitoring in era of cloud computing" covers the topics:
1. What is Monitoring
2. Ceilometer
- Architecture
- Agents (Compute/Central)
- Storage & API
- Quick Demo
3. Monasca
- Architecture
- Events/Messages
- Storage & API
- Quick Demo
Everyone wants observability into their system, but find themselves with too many vendors and tools, each with its own API, SDK, agent and collectors.
In this talk I will present OpenTelemetry, an ambitious open source project with the promise of a unified framework for collecting observability data. With OpenTelemetry you could instrument your application in a vendor-agnostic way, and then analyze the telemetry data in your backend tool of choice, whether Prometheus, Jaeger, Zipkin, or others.
I will cover the current state of the various projects of OpenTelemetry (across programming languages, exporters, receivers, protocols), some of which not even GA yet, and provide useful guidance on how to get started with it.
What is observability and how is it different from traditional monitoring? How do we effectively monitor and debug complex, elastic microservice architectures? In this interactive discussion, we’ll answer these questions. We’ll also introduce the idea of an “observability pipeline” as a way to empower teams following DevOps practices. Lastly, we’ll demo cloud-native observability tools that fit this “observability pipeline” model, including Fluentd, OpenTracing, and Jaeger.
Observability has emerged as one of the hottest topics on the DevOps landscape. Organizations seek to improve visibility into their cloud infrastructure and applications and identify production issues that may negatively impact #customerexperience.
➡️ But what are some of the best practices for scaling observability for modernapplications?
➡️ What challenges are #cloudplatforms facing?
Explore how to overcome the challenges and unlock speed, observability, and automation across your DevOps lifecycle.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk covers the fundamental concepts of observability and then demonstrates how to instrument your applications using the OpenTelemetry libraries.
More Than Monitoring: How Observability Takes You From Firefighting to Fire P...DevOps.com
For some, observability is just a hollow rebranding of monitoring, for others it’s monitoring on steroids. But what if we told you observability is the new way to find out why—not just if—your distributed system or application isn’t working as expected? Today, we see that traditional monitoring approaches can fall short if a system or application doesn’t adequately externalize its state.
This is truer as workloads move into the cloud and leverage ephemeral technologies, such as microservices and containers. To reach observability, IT and DevOps teams need to correlate different sources from logs, metrics, traces, events and more. This becomes even more challenging when defining the online revenue impact of a failed container—after all, this is what really matters to the business.
This webinar will cover:
The differences between observability and monitoring
Why it is a bigger challenge in a multicloud and containerized world
How observability results in less firefighting and more fire prevention
How new platforms can help gain observability (on premises and in the cloud) for containers, microservices and even SAP or mainframes
Is your company built on software? How do you know if your customer's experience is slow and sucks? How do you debug slowness or troubleshoot an incident? Observability! David Mitchell, VP of Engineering at Datadog will talk to use about Observability, why it's important, what it is and how Datadog helps reduce toil in your environment.
GDG Cloud Southlake #13
The pervasiveness of cloud and containers has led to systems that are much more distributed and dynamic in nature. Highly elastic microservice and serverless architectures mean containers spin up on demand and scale to zero when that demand goes away. In this world, servers are very much cattle, not pets. This shift has exposed deficiencies in some of the tools and practices we used in the world of servers-as-pets. Specifically, there are questions around how we monitor and debug these types of systems at scale. And with the rise of DevOps and product mindset, making data-driven decisions is becoming increasingly important for agile development teams.
In this talk, we discuss a new approach to system monitoring and data collection: the observability pipeline. For organizations that are heavily siloed, this approach can help empower teams when it comes to operating their software. The observability pipeline provides a layer of abstraction that allows you to get operational data such as logs and metrics everywhere it needs to be without impacting developers and the core system. Unlocking this data can also be a huge win for the business with things like auditability, business analytics, and pricing. Lastly, it allows you to change backing data systems easily or test multiple in parallel. With the amount of data and the number of tools modern systems demand these days, we'll see how the observability pipeline becomes just as essential to the operations of a service as the CI/CD pipeline.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk covers the latest concepts in observability and then demonstrates how to configure and deploy various OpenTelemetry components to effectively meet your SLO's.
My contribution to the "Grafana & Friends" Meetup.
This presentation goes into the context in the Observability landscape, the basics of OpenTelemetry with its signals and lookout what to expect next.
Whether you’re an enterprise migrating to cloud native or born in the cloud, most of today’s APM and Observability tools don’t support how your engineers and DevOps teams need to develop, deploy, and support their software. Observability needs to shift left and reflect the modern way companies organize their development teams and their vital interdependencies.
Chronosphere is the only vendor addressing the unique requirements for observability in a cloud native world. Join this webinar to learn:
- What cloud native observability is and how it is different from the promises made by traditional cloud APM and observability vendors
- How to use cloud native observability to do more “Dev” and less “Ops” so you can dramatically improve developer and engineer workflows and productivity
- How to make on-call shifts less stressful so your engineers aren’t getting burned out
Modern cloud-native applications are incredibly complex systems. Keeping the systems healthy and meeting SLAs for our customers is crucial for long-term success. In this session, we will dive into the three pillars of observability - metrics, logs, tracing - the foundation of successful troubleshooting in distributed systems. You'll learn the gotchas and pitfalls of rolling out the OpenTelemetry stack on Kubernetes to effectively collect all your signals without worrying about a vendor lock in. Additionally we will replace parts of the Prometheus stack to scrape metrics with OpenTelemetry collector and operator.
This presentation gives audiences a broad viewpoint from old to modern architecture. How Kubernetes and service mesh (istio) can help developers in those missions:
- Explain from traditional to modern architecture. The role of Kubernetes in modern architecture.
- Build basic k8s components from the ground up with illustrations: Pod; Node; Service; ReplicaSet; Deployment; Namespace; Ingress ...
- Kubernetes under the developer viewpoint: write a YAML application file and deploy k8s application to the cluster.
- Kubernetes advanced concepts: master node design, how does the auto-scale for pods/nodes work, Kubernetes networking model.
- Discuss microservice challenges. The role of the service mesh in the microservice ecosystem.
- Introduce Envoy, istio and their application in the service mesh.
Everything You wanted to Know About Distributed TracingAmuhinda Hungai
In the age of microservices, understanding how applications are executing in a highly distributed environment can be complicated. Looking at log files only gives a snapshot of the whole story and looking at a single service in isolation simply does not give enough information. Each service is just one side of a bigger story. Distributed tracing has emerged as an invaluable technique that succeeds in summarizing all sides of the story into a shared timeline. Yet deploying it can be quite challenging, especially in the large scale, polyglot environments of modern companies that mix together many different technologies. During this session, we will take a look at patterns and means to implement Tracing for services. After introducing the basic concepts we will cover how the tracing model works, and how to safely use it in production to troubleshoot and diagnose issues.
This talk is about monitoring with Prometheus. A progression is shown from monitoring concept, to Micrometer, Prometheus and Grafana.
Presented at Alithya by Richard Langlois and Gervais Naoussi, on September 19th, 2018
Webinar Monitoring in era of cloud computingCREATE-NET
The webinar "Monitoring in era of cloud computing" covers the topics:
1. What is Monitoring
2. Ceilometer
- Architecture
- Agents (Compute/Central)
- Storage & API
- Quick Demo
3. Monasca
- Architecture
- Events/Messages
- Storage & API
- Quick Demo
The Istio service mesh provides a highly extensible platform to connect, manage, and secure microservices. Istio’s highly extensible nature is one of the main selling points as it allows you to enforce your own organization-specific policies across large fleets of microservices. At the same time, new technology always has a learning curve, and with all this extensibility and generality the task can be quite daunting.
In this talk, Limin Wang (Software Engineer at Google) and Torin Sandall (Technical Lead of the Open Policy Agent project) explain how Istio’s Mixer works and lead a deep dive into Mixer Adapter development. The talk shows (with demos) how the Mixer Adapter model enables custom policy enforcement and how the model is used to integrate third party policy engines like the Open Policy Agent.
This talk is targeted at platform engineers interested in using the Istio service mesh to enforce custom policies in their microservices. The talk also provides new ideas about the kinds of policies that can be enforced in Istio today.
Introduction to Reactive Extensions (Rx)Tamir Dresher
Presentations from the june meeting of IDNDUG
http://ariely.info/Communities/IDNDUG/IDNDUG19thJune2013/tabid/171
The Reactive Extensions (Rx) is a library for composing asynchronous and event-based programs using observable sequences and LINQ-style query operators. Using Rx, developers represent asynchronous data streams with Observables, query asynchronous data streams using LINQ operators, andparameterize the concurrency in the asynchronous data streams using Schedulers. Simply put, Rx = Observables + LINQ + Schedulers
Algorithmic Trading Deutsche Borse Public DatasetMarjan Ahmed
AWS hosted back-testing framework for algorithmic trading. The objective is to analyze a given data set of equities containing price-volume data and develop medium to high frequency strategies for trading equities quickly via cloud computing. A simple web interface will be constructed allowing users to control and tweak trading parameter settings, and see in-sample and out-of-sample trading performance (i.e., hypothetical profit and loss, tradings costs, turnover, portfolio risk and Sharpe ratio).
This report details the findings, implementation and research method of the teams algorithmic trading model developed using machine learning frameworks implemented leveraging AWS cloud computing infrastructure.
Monitoring in Big Data Platform - Albert Lewandowski, GetInDataGetInData
Did you like it? Check out our blog to stay up to date: https://getindata.com/blog
The webinar was organized by GetinData on 2020. During the webinar we explaned the concept of monitoring and observability with focus on data analytics platforms.
Watch more here: https://www.youtube.com/watch?v=qSOlEN5XBQc
Whitepaper - Monitoring ang Observability for Data Platform: https://getindata.com/blog/white-paper-big-data-monitoring-observability-data-platform/
Speaker: Albert Lewandowski
Linkedin: https://www.linkedin.com/in/albert-lewandowski/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
FOSDEM 2019: M3, Prometheus and Graphite with metrics and monitoring in an in...Rob Skillington
The world in which we monitor software is growing more complex every year. There are increasingly more ways to run server-side software, with many more independent services and more points of failures, the list goes on! On the plus side, there’s a lot of great tools and patterns being developed to try and make things simple to assess and understand. This talk covers how metrics and monitoring can be leveraged in a variety of different ways, auto-discovering applications and their usage of databases, caches, load balancers, etc, setting up and tearing down dashboards and monitoring automatically for services and instances, and more.
We’ll also talk about how you can accomplish all this with a global view of your systems using both Prometheus and Graphite with M3, our open source metrics platform. We’ll take a deep dive look at how we use M3DB, distributed aggregation with the M3 aggregator and the M3 Kubernetes operator to horizontally scale a metrics platform in a way that doesn’t cost outrageous amounts to run with a system that’s still sane to operate with petabytes of metrics data.
Talk from https://stackconf.eu/talks/how-to-reduce-expenses-on-monitoring-with-victoriametrics/
Given recent economic changes, cost efficiency has become a top priority for many businesses. This is especially important for monitoring because the nature of telemetry data tends to exponential growth. Many monitoring solutions are now switching their focus to optimize costs. The talk will cover open-source instruments from VictoriaMetrics ecosystem for improving monitoring cost-efficiency.
Compression optimization. While ZSTD compression and time series specific techniques like delta-encoding are great, there is still room for improvement. I’ll explain what else can be done to reduce disk footprint for long-term storage.
Extra compression on data transferring between metrics collectors and TSDB. I’ll explain how VictoriaMetrics collector reduces the traffic volume by 4 times.
Pre-computing for telemetry data on collectors, frequently referred to as edge computing. In VictoriaMetrics it is named as streaming aggregation and allows collectors to pre-compute data, reducing its resolution and cardinality before it is pushed to the database. This is especially important for Prometheus-like systems because streaming aggregation is compatible with Prometheus RemoteWrite protocol and can be used with any system which supports it.
Cardinality explorer. Interface, which provides useful insights into data stored by the TSDB. It helps to identify the most expensive metrics or labels and see how they have changed in time.
Query tracing. This feature provides details about all the stages of query execution, including time spent on index lookups, disk reads, data transfer, computation, and memory expenses. This is similar to SQL EXPLAIN feature, and helps to improve the performance of read queries.
Compute efficiency. VictoriaMetrics components for collecting and storing telemetry data consume fewer resources compared to components from Prometheus ecosystem. It may sound like competition or bragging, but this is a real reason why people migrate from Prometheus to VictoriaMetrics – to cut their infrastructure costs by 2-3 times.
All the features listed above are open-source and are available for everyone to use. The talk will be mostly concentrated on typical use cases in monitoring and elegant ways to make things more efficient.
"Используем MetricKit в бою" / Марина Звягина (Vivid Money)Egor Petrov
Этот доклад будет максимально прикладным. Насколько MetricKit
хорош? Какие данные действительно помогут оптимизировать работу приложения? Как подружить MetricKit с другими метриками?
В приложении Vivid используется MetricKit и мы уже решили эти вопросы и многие другие.
OSMC 2019 | Monitoring Cockpit for Kubernetes Clusters by Ulrike KlusikNETWAYS
Monitoring Kubernetes Clusters with Prometheus is state of the art. The difficulty is to find the significant metrics from the vast amount of available metrics. This talk shows a Monitoring Cockpit defined to get a quick overview of the cluster health and usage. It uses the Standard Metrics available for Kubernetes/OpenShift Clusters and their standard services. The monitoring solution is based on Prometheus, using InfluxDB for central long term storage and Grafana.
QuickStart your Sumo Logic service with this exclusive webinar. At these monthly live events you will learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights.
Video: https://www.sumologic.com/online-training/#QuickStart
Summary Create an Object-Oriented program that creates a simulator an.pdfallwinsupport
Summary Create an Object-Oriented program that creates a simulator and that allows the user to
place sensor(s) across Sheridan's building(s) to monitor the different levels of CO2. In addition,
practice program flow control statements to branch and repeat statements as needed. Moreover,
divide the business logic appropriately between classes and create methods as needed.
Application Description Write a program based on the Object Oriented (OO) paradigm that
displays the sensors'/sensor's data/information for each Sheridan's building. This information (or
data) includes the sensor's 2D position, the different CO2 levels in PPM, and the average
reading(s) for one or more readings. The application will ask for the following: 1) the number of
buildings that needs to be monitored in terms of the CO2 levels in PPM, 2) the building name (at
least one building), and 3) the number of sensors deployed for each building. Afterwards, the
program will ask the following for each building: 1) the number of days that are monitored, and
2) the CO2 reading(s) (PPM) for each day. Detailed Requirements: Initialization: For each class,
define all required field variables (or attributes) and methods. Define and implement the required
accessor and mutator methods. Ensure you detect and correct syntax errors early. Commit
changes often to demonstrate that you followed stepwise refinements process.
Part I Business Iogic (each class is saved in a separate fille as a module): assignment, label the
relationships with their name: USES, HAS-A and IS-A. Take a screenshot of the diagram and
paste it on a document called UML Student Name. Application Class (main class): Part III: Error
Handling, Using standard error checking (if-else) to ensure the input is vulid - Define a start(..)
method that runs the Sheridan System. both in terms of range and type of data entered. This
includes the number of buildings, number SheridanSystem Class: of sensors, buildings" names,
the number of days and the number of CO2 readings. Moreover, the building names do not any
numerical values. The application should not crash at any point - Define noOfBuild attribute. due
to data input i processing. If the recovery from error(s) is not possible, then at least inform -
Define the method run(...) that creates a number of buildings. the user about the error(s) and
terminate the application. A sample of outputs are placed at the - Upon the creation of buildings,
create one or more sensors via the createSensors(...) end of this document to clarify those cases.
method. This method is a member of the Building class below. Part IV; Program Development
Process, The project is to be developed iteratively in small Building Class: increments. Code
must be version controlled using GlI using BitBucket. Each milestone must - Define
noOfSensors, listOfSensors, and buildName attributes. have at a minimum one commit at the end
of the milestone. For best evaluation, ensure changes - Define the method createSensors(.
How to Monitor Application Performance in a Container-Based WorldKen Owens
Monitoring applications that consists of multiple containers is not easy or available as part of any container solution or orchestration platform. This talk looks at how to address application performance leveraging business service level objectives and the architecture for implementing the solution. The solution has been prototyped at ciscoshipped.io and we would love your thoughts.
Brand new to Sumo Logic? Learn how to get started and get the most out of your service. Learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights.
Video: https://www.sumologic.com/online-training/#QuickStart
People are leaving WhatsApp for Signal and Telegram. Privacy becomes important more than ever. Have we ever stepped back and rethought carefully how these applications handle end-users’ privacy? Is that a myth; a promise; or back-up by some scientific evidence? How can we, as an end-user, can verify and make sure these claims?
This presentation will explain the history of the development of Signal and Telegram; and how they handle user’s data privacy under the technical microscope.
Prerequisites: Some fundamental knowledge about cryptography: symmetric encryption; asymmetric encryption; public key; private key;
Consensus and Raft Algorithm in Distributed SystemThao Huynh Quang
A modern computing system requires multiple components distributed on different machines to provide scalability, high availability, fault tolerance, and low latency. Therefore, consensus is essential when communicating between nodes to agree on some data value required during computation.
There are many examples of consensus around our tooling:
- Google Chubby uses Paxos, which is a consensus algorithm.
- Kubernetes uses etcd as the backing store for all cluster data. Etcd uses Raft, which is a consensus algorithm.
- Hadoop; Kafka uses ZooKeeper for service discovery; leader’s election, ... ZooKeeper uses a Paxos-variant algorithm.
- Blockchain cannot exist without consensus algorithms such as Proof-of-work; Proof-of-stake; ...
As the result, knowledge of consensus in the distributed system is crucial to understand the behavior of those systems. This presentation will:
Brief introduction about the consensus; challenges and achieved result.
Raft algorithm - the main consensus algorithm used in most of the recent systems.
Some references to get our hand wet on this topic:
https://medium.com/@isuruboyagane.16/what-is-consensus-in-distributed-system-6d51d0802b8c
https://www.youtube.com/watch?v=5m3eBWKjHtM&ab_channel=HasgeekTV
Consensus and Raft algorithm (Vietnamese version)Thao Huynh Quang
Giới thiệu tổng quan về bài toán đồng thuận trong hệ thống phân tán: Two General Problem; FLP;...
Trình bày về thuật toán Raft:
- Leader election
- Log Replication
- Safety property
Các paper / blog ... tham khảo.
- Discuss Java pros and cons
- Kool features in Kotlin.
- How to use Kotlin in Android development.
- How to migrate old Android java code to new Kotlin code.
Designed and presented by Telco internships.
- Explain all basic components in Git: commit, commit hash, branch, git logs, reflogs ...
- Explain some common use operations and the differences between them: merge, rebase, revert, reset, pull, push ...
- How to use GitHub in daily work.
- Discuss the Android Jetpack: New Android libraries officially developed by Google.
- Discuss the Room persistence library in Jetpack. How does Room library help developer life easier when working with databases.
This presentation introduces every aspects of the Kafka ecosystem:
- Concepts: explain all misleading concepts such as topic vs partition vs replication, producer vs consumer vs consumer group, group leader vs group coordinator, ...
- Advanced concepts: delivery semantic; idempotent producers; isolation levels; differences between the offsets such as High Watermark, Log End Offset, Last Stable Offset ...
- Kafka architecture: explain all Kafka components such as brokers, controllers, zookeeper, ...
- Overview of Kafka security: TLS/SSL, SASL, Kerberos, ...
- Overview of Kafka ecosystem: Kafka Stream, Kafka Connect, Schema Registry, monitoring tools.
- Kafka in Golang: How to use Kafka client in Golang.
- Comparison with other message queues such as RabbitMQ.
This is the short presentation of how does the theorem works at a high level.
This presentation introduces Metamask, Infura, Etherscan, ... and how those systems interact with smart contracts.
- Discuss coroutines and channels in modern architecture.
- Concurrency vs Parallelism with real-world examples.
- Simple to advanced concurrency patterns in Kotlin.
Most developers are familiar with making network requests using RESTFUL APIs. However, there are some disadvantages to this approach: very coupling between the backend and the client. For instance, they must communicate back with the backend team when a mobile client wants to change or add some fields to the response. The time for discussions among teams and service deployment might delay project deadlines, hence affecting business opportunities. This topic will discuss the newer approach, GraphQL, and how to apply libraries to the Android world to solve this problem.
- Discussion about client server communication such as JSON/SOAP and RPC.
- Advantages/Disadvantages of GRPC in micro service, developing application ...
- How to apply GRPC in Android application. Providing source code for both client and server side.
Slide for speaking at Droidcon Vietnam 2017
Introduction:
Million of android developers around the world are making great apps. But very few really take care about their compiled code really looks like. How do reverse engineers view their app under different perspective.
This speaking will explain in detail about android reverse engineering from the ground up. Attendee will learn about reading byte code, modify and compile apk file, hooking framework and all additional tools for reverse engineering life.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Multiple Your Crypto Portfolio with the Innovative Features of Advanced Crypt...Hivelance Technology
Cryptocurrency trading bots are computer programs designed to automate buying, selling, and managing cryptocurrency transactions. These bots utilize advanced algorithms and machine learning techniques to analyze market data, identify trading opportunities, and execute trades on behalf of their users. By automating the decision-making process, crypto trading bots can react to market changes faster than human traders
Hivelance, a leading provider of cryptocurrency trading bot development services, stands out as the premier choice for crypto traders and developers. Hivelance boasts a team of seasoned cryptocurrency experts and software engineers who deeply understand the crypto market and the latest trends in automated trading, Hivelance leverages the latest technologies and tools in the industry, including advanced AI and machine learning algorithms, to create highly efficient and adaptable crypto trading bots
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Strategies for Successful Data Migration Tools.pptxvarshanayak241
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
38. OpenCensus sample rules
The OpenCensus use the head-based sampling with following rules:
1. If the span is a root Span:
• If a "span-scoped" Sampler is provided, use it to determine the sampling decision.
• Else use the global default Sampler to determine the sampling decision.
2. If the span is a child of a remote Span:
• If a "span-scoped" Sampler is provided, use it to determine the sampling decision.
• Else use the global default Sampler to determine the sampling decision.
3. If the span is a child of a local Span:
• If a "span-scoped" Sampler is provided, use it to determine the sampling decision.
• Else keep the sampling decision from the parent.
Disadvantages:
- Might lost some useful data.
- Can be Wixed by using the tail-based approach on the OpenCensus collector.
References:
- https://github.com/census-instrumentation/opencensus-specs/blob/master/
trace/Sampling.md
- https://sWlanders.net/2019/04/17/intelligent-sampling-with-opencensus/
71. Sample project
1. Repository: https://github.com/tsocial/distributed_tracing_demo
- Test with Gorm/Redis
- Test tracing with console exporter
- Test with Jaeger /Prometheus
- Call external service
- Call internal service
- TODO: test with OpenCensus service
2. Repository:
https://github.com/census-instrumentation/opencensus-service/blob/master/demos/trace/
docker-compose.yaml
- Test with OpenCensus service
- Multiple internal services
- Jaeger / Prometheus / Zipkin …