So you are using Terraform to manage your infrastructure, fantastic! However have you ever accidentally destroyed your production setup? Or managed to change some part of your infrastructure you were not expecting to?
This talk explores some common pain points experienced by users on different parts of their Terraform journey and provides insight into how you can evolve your Terraform setup to manage and address these challenges.
This document discusses Terraform, an open-source tool that allows users to define and provision infrastructure resources in a declarative configuration file. It summarizes that Terraform allows users to build, change, and destroy infrastructure components like compute instances, storage buckets, and networking through declarative configuration files, enabling an infrastructure-as-code approach that is easy to version, track changes for, and integrate with continuous delivery practices.
This document contains notes from a talk on advanced Terraform techniques. It discusses using Terraform for infrastructure as code to deploy resources across multiple environments like development, staging, and production. It also mentions techniques like separating code into modules, using variables to parameterize configurations, and integrating Terraform with other DevOps tools like Ansible.
We've added the presentation used by John Walter, Solution Architect for Red Hat's Training and Certification team, from our Accelerating with Ansible webinar. He discussed the emergence of radically simple Ansible automation and answered questions from attendees. Learn how Ansible automates cloud provisioning, configuration management, application deployment, intra-service orchestration, and many other IT needs. Also learn how Ansible is designed for multi-tier deployments from day one and how Ansible models your IT infrastructure by describing how all your systems inter-relate, rather than just managing one system at a time.
This document provides an agenda and notes for a 3-day AWS, Terraform, and advanced techniques training. Day 1 covers AWS networking, scaling techniques, automation with Terraform and covers setting up EC2 instances, autoscaling groups, and load balancers. Day 2 continues EC2 autoscaling, introduces Docker, ECS, monitoring, and continuous integration/delivery. Topics include IAM, VPC networking, NAT gateways, EC2, autoscaling policies, ECS clusters, Docker antipatterns, monitoring servers/applications/logs, and Terraform code structure. Day 3 will cover Docker, ECS, configuration management, Vault, databases, Lambda, and other advanced AWS and DevOps topics.
Terraform is an open source tool for building, changing, and versioning infrastructure safely and efficiently. It allows users to define and provision a datacenter infrastructure using a high-level configuration language known as HashiCorp Configuration Language. Some key features of Terraform include supporting multiple cloud providers and services, being declarative and reproducible, and maintaining infrastructure as code with immutable infrastructure. It works by defining configuration files that specify what resources need to be created. The configuration is written in HCL. Terraform uses these files to create and manage infrastructure resources like VMs, network, storage, containers and more across multiple cloud platforms.
This document discusses an introduction to Terraform infrastructure as code. It covers what Terraform is, its key features like being declarative and reusable, pros and cons like reducing human error but having a high entry barrier. It discusses major providers supported by Terraform including cloud providers, software, and monitoring tools. It concludes with basic steps for getting started with Terraform like installation, AWS profile setup, creating demo files, and executing commands to provision a VPC on AWS.
This document discusses Terraform, an open-source tool that allows users to define and provision infrastructure resources in a declarative configuration file. It summarizes that Terraform allows users to build, change, and destroy infrastructure components like compute instances, storage buckets, and networking through declarative configuration files, enabling an infrastructure-as-code approach that is easy to version, track changes for, and integrate with continuous delivery practices.
This document contains notes from a talk on advanced Terraform techniques. It discusses using Terraform for infrastructure as code to deploy resources across multiple environments like development, staging, and production. It also mentions techniques like separating code into modules, using variables to parameterize configurations, and integrating Terraform with other DevOps tools like Ansible.
We've added the presentation used by John Walter, Solution Architect for Red Hat's Training and Certification team, from our Accelerating with Ansible webinar. He discussed the emergence of radically simple Ansible automation and answered questions from attendees. Learn how Ansible automates cloud provisioning, configuration management, application deployment, intra-service orchestration, and many other IT needs. Also learn how Ansible is designed for multi-tier deployments from day one and how Ansible models your IT infrastructure by describing how all your systems inter-relate, rather than just managing one system at a time.
This document provides an agenda and notes for a 3-day AWS, Terraform, and advanced techniques training. Day 1 covers AWS networking, scaling techniques, automation with Terraform and covers setting up EC2 instances, autoscaling groups, and load balancers. Day 2 continues EC2 autoscaling, introduces Docker, ECS, monitoring, and continuous integration/delivery. Topics include IAM, VPC networking, NAT gateways, EC2, autoscaling policies, ECS clusters, Docker antipatterns, monitoring servers/applications/logs, and Terraform code structure. Day 3 will cover Docker, ECS, configuration management, Vault, databases, Lambda, and other advanced AWS and DevOps topics.
Terraform is an open source tool for building, changing, and versioning infrastructure safely and efficiently. It allows users to define and provision a datacenter infrastructure using a high-level configuration language known as HashiCorp Configuration Language. Some key features of Terraform include supporting multiple cloud providers and services, being declarative and reproducible, and maintaining infrastructure as code with immutable infrastructure. It works by defining configuration files that specify what resources need to be created. The configuration is written in HCL. Terraform uses these files to create and manage infrastructure resources like VMs, network, storage, containers and more across multiple cloud platforms.
This document discusses an introduction to Terraform infrastructure as code. It covers what Terraform is, its key features like being declarative and reusable, pros and cons like reducing human error but having a high entry barrier. It discusses major providers supported by Terraform including cloud providers, software, and monitoring tools. It concludes with basic steps for getting started with Terraform like installation, AWS profile setup, creating demo files, and executing commands to provision a VPC on AWS.
Infrastructure-as-Code (IaC) using TerraformAdin Ermie
Learn the benefits of Infrastructure-as-Code (IaC), what Terraform is and why people love it, along with a breakdown of the basics (including live demo deployments). Then wrap up with a comparison of Azure Resource Manager (ARM) templates versus Terraform, consider some best practices, and walk away with some key resources in your Terraform learning adventure.
Terraform Best Practices - DevOps Unicorns 2019Anton Babenko
Terraform best practices include using modules to break infrastructure into reusable components, structuring configurations in a one-in-one approach with directories for each module, and avoiding workspaces in favor of additional modules. Terraform 0.12 benefits developers most through features like loops and conditionals that enable more flexible modules, while users appreciate minor syntax improvements. The presentation emphasizes reusability, separation of concerns, and standardization through open-source modules.
My talk at FullStackFest, 4.9.2017. Become more familiar with managing infrastructure using Terraform, Packer and deployment pipeline. Code repository - https://github.com/antonbabenko/terraform-deployment-pipeline-talk
Apache Iceberg: An Architectural Look Under the CoversScyllaDB
Data Lakes have been built with a desire to democratize data - to allow more and more people, tools, and applications to make use of data. A key capability needed to achieve it is hiding the complexity of underlying data structures and physical data storage from users. The de-facto standard has been the Hive table format addresses some of these problems but falls short at data, user, and application scale. So what is the answer? Apache Iceberg.
Apache Iceberg table format is now in use and contributed to by many leading tech companies like Netflix, Apple, Airbnb, LinkedIn, Dremio, Expedia, and AWS.
Watch Alex Merced, Developer Advocate at Dremio, as he describes the open architecture and performance-oriented capabilities of Apache Iceberg.
You will learn:
• The issues that arise when using the Hive table format at scale, and why we need a new table format
• How a straightforward, elegant change in table format structure has enormous positive effects
• The underlying architecture of an Apache Iceberg table, how a query against an Iceberg table works, and how the table’s underlying structure changes as CRUD operations are done on it
• The resulting benefits of this architectural design
Developing Terraform Modules at Scale - HashiTalks 2021TomStraub5
This document discusses best practices for developing Terraform modules at scale. It covers key topics like defining module structure, using modules, managing module versions and upgrades, discoverability, and release processes. The goal is to help make modules reusable, versioned, and easily consumed as infrastructure codebases grow in size and complexity.
Infrastructure-as-Code (IaC) Using Terraform (Intermediate Edition)Adin Ermie
In this presentation, we will cover intermediate Terraform topics including alternative providers, collection types, loops and conditionals, and resource lifecycles. We will also focus on reusability with a discussion on modules, data sources, and remote state (including live demo examples).
Finally, we start the initial look into a full DevOps process with a quick review of Workspaces and Terraform Cloud; and wrap everything up with some key takeaway learning resources in your Terraform learning adventure.
NOTE: A recording this presentation can be found here: https://youtu.be/0CEF4eZ6HiQ
The document discusses MapR cluster management using the MapR CLI. It provides examples of starting and stopping a MapR cluster, managing nodes, volumes, mirrors and schedules. Specific examples include creating volumes, linking mirrors to volumes, syncing mirrors, moving volumes and nodes to different topologies, and creating schedules to automate tasks.
Terraform modules and best-practices - September 2018Anton Babenko
Slides for my "Terraform modules and best-practices" talk on meetups during September 2018.
Some links from the slides:
https://www.terraform-best-practices.com/
https://cloudcraft.co/
https://github.com/terraform-aws-modules/
https://github.com/antonbabenko/modules.tf-lambda
How to test infrastructure code: automated testing for Terraform, Kubernetes,...Yevgeniy Brikman
This talk is a step-by-step, live-coding class on how to write automated tests for infrastructure code, including the code you write for use with tools such as Terraform, Kubernetes, Docker, and Packer. Topics covered include unit tests, integration tests, end-to-end tests, test parallelism, retries, error handling, static analysis, and more.
This document provides an overview of Terraform including its key features and how to install, configure, and use Terraform to deploy infrastructure on AWS. It covers topics such as creating EC2 instances and other AWS resources with Terraform, using variables, outputs, and provisioners, implementing modules and workspaces, and managing the Terraform state.
Tao Feng gave a presentation on Airflow at Lyft. Some key points:
1) Lyft uses Apache Airflow for ETL workflows with over 600 DAGs and 800 DAG runs daily across three AWS Auto Scaling Groups of worker nodes.
2) Lyft has customized Airflow with additional UI links, DAG dependency graphs, and integration with internal tools.
3) Lyft is working to improve the backfill experience, support DAG-level access controls, and explore running Airflow with Kubernetes executors.
4) Tao discussed challenges like daylight saving time issues and long-running tasks occupying slots, and thanked other Lyft engineers contributing to Airflow.
You've seen the basic 2-stage example Spark Programs, and now you're ready to move on to something larger. I'll go over lessons I've learned for writing efficient Spark programs, from design patterns to debugging tips.
The slides are largely just talking points for a live presentation, but hopefully you can still make sense of them for offline viewing as well.
Terraform is an Infrastructure Automation tools. This can work equally good for on-premises, public cloud, private cloud, hybrid-cloud and multi-cloud infrastructure.
Visit us for more at www.zekeLabs.com
Infrastructure-as-Code (IaC) Using Terraform (Advanced Edition)Adin Ermie
In this new presentation, we will cover advanced Terraform topics (full-on DevOps). We will compare the deployment of Terraform using Azure DevOps, GitHub/GitHub Actions, and Terraform Cloud. We wrap everything up with some key takeaway learning resources in your Terraform learning adventure.
NOTE: A recording of this presenting is available here: https://www.youtube.com/watch?v=fJ8_ZbOIdto&t=5574s
1) Columnar formats like Parquet, Kudu and Arrow provide more efficient data storage and querying by organizing data by column rather than row.
2) Parquet provides an immutable columnar format well-suited for storage, while Kudu allows for mutable updates but is optimized for scans. Arrow provides an in-memory columnar format focused on CPU efficiency.
3) By establishing common in-memory and on-disk columnar standards, Arrow and Parquet enable more efficient data sharing and querying across systems without serialization overhead.
This document discusses Terraform, an open-source infrastructure as code tool. It begins by explaining how infrastructure can be defined and managed as code through services that have APIs. It then provides an overview of Terraform, including its core concepts of providers, resources, and data sources. The document demonstrates Terraform's declarative configuration syntax and process of planning and applying changes. It also covers features like modules, state management, data sources, and developing custom plugins.
22nd Athens Big Data Meetup - 1st Talk - MLOps Workshop: The Full ML Lifecycl...Athens Big Data
Title: MLOps Workshop: The Full ML Lifecycle - How to Use ML in Production
Speakers: Spyros Cavadias (https://www.linkedin.com/in/spyros-cavadias/), Konstantinos Pittas (https://www.linkedin.com/in/konstantinos-pittas-83310270/), Thanos Gkinakos (https://www.linkedin.com/in/thanos-gkinakos-03582a128/)
Date: Saturday, December 17, 2022
Event: https://www.meetup.com/athens-big-data/events/289927468/
Declarative & workflow based infrastructure with TerraformRadek Simko
Terraform allows users to define infrastructure as code to provision resources across multiple cloud platforms. It aims to describe infrastructure in a configuration file, provision resources efficiently by leveraging APIs, and manage the full lifecycle from creation to deletion. Key features include supporting composability across different infrastructure tiers, using a graph-based approach to parallelize operations for efficiency, and managing state to track resource unique IDs and allow recreating resources. Providers enable connectivity to different cloud APIs while resources define the specific infrastructure components and their properties.
OSDC 2015: Mitchell Hashimoto | Automating the Modern Datacenter, Development...NETWAYS
Physical, virtual, containers. Public cloud, private cloud, hybrid cloud. IaaS, PaaS, SaaS. These are the choices that we're faced with when architecting a datacenter of today. And the choice is not one or the other; it is often a combination of many of these. How do we remain in control of our datacenters? How do we deploy and configure software, manage change across disparate systems, and enforce policy/security? How do we do this in a way that operations engineers and developers alike can rejoice in the processes and workflow?
In this talk, I will discuss the problems faced by the modern datacenter, and how a set of open source tools including Vagrant, Packer, Consul, and Terraform can be used to tame the rising complexity curve and provide solutions for these problems.
Infrastructure-as-Code (IaC) using TerraformAdin Ermie
Learn the benefits of Infrastructure-as-Code (IaC), what Terraform is and why people love it, along with a breakdown of the basics (including live demo deployments). Then wrap up with a comparison of Azure Resource Manager (ARM) templates versus Terraform, consider some best practices, and walk away with some key resources in your Terraform learning adventure.
Terraform Best Practices - DevOps Unicorns 2019Anton Babenko
Terraform best practices include using modules to break infrastructure into reusable components, structuring configurations in a one-in-one approach with directories for each module, and avoiding workspaces in favor of additional modules. Terraform 0.12 benefits developers most through features like loops and conditionals that enable more flexible modules, while users appreciate minor syntax improvements. The presentation emphasizes reusability, separation of concerns, and standardization through open-source modules.
My talk at FullStackFest, 4.9.2017. Become more familiar with managing infrastructure using Terraform, Packer and deployment pipeline. Code repository - https://github.com/antonbabenko/terraform-deployment-pipeline-talk
Apache Iceberg: An Architectural Look Under the CoversScyllaDB
Data Lakes have been built with a desire to democratize data - to allow more and more people, tools, and applications to make use of data. A key capability needed to achieve it is hiding the complexity of underlying data structures and physical data storage from users. The de-facto standard has been the Hive table format addresses some of these problems but falls short at data, user, and application scale. So what is the answer? Apache Iceberg.
Apache Iceberg table format is now in use and contributed to by many leading tech companies like Netflix, Apple, Airbnb, LinkedIn, Dremio, Expedia, and AWS.
Watch Alex Merced, Developer Advocate at Dremio, as he describes the open architecture and performance-oriented capabilities of Apache Iceberg.
You will learn:
• The issues that arise when using the Hive table format at scale, and why we need a new table format
• How a straightforward, elegant change in table format structure has enormous positive effects
• The underlying architecture of an Apache Iceberg table, how a query against an Iceberg table works, and how the table’s underlying structure changes as CRUD operations are done on it
• The resulting benefits of this architectural design
Developing Terraform Modules at Scale - HashiTalks 2021TomStraub5
This document discusses best practices for developing Terraform modules at scale. It covers key topics like defining module structure, using modules, managing module versions and upgrades, discoverability, and release processes. The goal is to help make modules reusable, versioned, and easily consumed as infrastructure codebases grow in size and complexity.
Infrastructure-as-Code (IaC) Using Terraform (Intermediate Edition)Adin Ermie
In this presentation, we will cover intermediate Terraform topics including alternative providers, collection types, loops and conditionals, and resource lifecycles. We will also focus on reusability with a discussion on modules, data sources, and remote state (including live demo examples).
Finally, we start the initial look into a full DevOps process with a quick review of Workspaces and Terraform Cloud; and wrap everything up with some key takeaway learning resources in your Terraform learning adventure.
NOTE: A recording this presentation can be found here: https://youtu.be/0CEF4eZ6HiQ
The document discusses MapR cluster management using the MapR CLI. It provides examples of starting and stopping a MapR cluster, managing nodes, volumes, mirrors and schedules. Specific examples include creating volumes, linking mirrors to volumes, syncing mirrors, moving volumes and nodes to different topologies, and creating schedules to automate tasks.
Terraform modules and best-practices - September 2018Anton Babenko
Slides for my "Terraform modules and best-practices" talk on meetups during September 2018.
Some links from the slides:
https://www.terraform-best-practices.com/
https://cloudcraft.co/
https://github.com/terraform-aws-modules/
https://github.com/antonbabenko/modules.tf-lambda
How to test infrastructure code: automated testing for Terraform, Kubernetes,...Yevgeniy Brikman
This talk is a step-by-step, live-coding class on how to write automated tests for infrastructure code, including the code you write for use with tools such as Terraform, Kubernetes, Docker, and Packer. Topics covered include unit tests, integration tests, end-to-end tests, test parallelism, retries, error handling, static analysis, and more.
This document provides an overview of Terraform including its key features and how to install, configure, and use Terraform to deploy infrastructure on AWS. It covers topics such as creating EC2 instances and other AWS resources with Terraform, using variables, outputs, and provisioners, implementing modules and workspaces, and managing the Terraform state.
Tao Feng gave a presentation on Airflow at Lyft. Some key points:
1) Lyft uses Apache Airflow for ETL workflows with over 600 DAGs and 800 DAG runs daily across three AWS Auto Scaling Groups of worker nodes.
2) Lyft has customized Airflow with additional UI links, DAG dependency graphs, and integration with internal tools.
3) Lyft is working to improve the backfill experience, support DAG-level access controls, and explore running Airflow with Kubernetes executors.
4) Tao discussed challenges like daylight saving time issues and long-running tasks occupying slots, and thanked other Lyft engineers contributing to Airflow.
You've seen the basic 2-stage example Spark Programs, and now you're ready to move on to something larger. I'll go over lessons I've learned for writing efficient Spark programs, from design patterns to debugging tips.
The slides are largely just talking points for a live presentation, but hopefully you can still make sense of them for offline viewing as well.
Terraform is an Infrastructure Automation tools. This can work equally good for on-premises, public cloud, private cloud, hybrid-cloud and multi-cloud infrastructure.
Visit us for more at www.zekeLabs.com
Infrastructure-as-Code (IaC) Using Terraform (Advanced Edition)Adin Ermie
In this new presentation, we will cover advanced Terraform topics (full-on DevOps). We will compare the deployment of Terraform using Azure DevOps, GitHub/GitHub Actions, and Terraform Cloud. We wrap everything up with some key takeaway learning resources in your Terraform learning adventure.
NOTE: A recording of this presenting is available here: https://www.youtube.com/watch?v=fJ8_ZbOIdto&t=5574s
1) Columnar formats like Parquet, Kudu and Arrow provide more efficient data storage and querying by organizing data by column rather than row.
2) Parquet provides an immutable columnar format well-suited for storage, while Kudu allows for mutable updates but is optimized for scans. Arrow provides an in-memory columnar format focused on CPU efficiency.
3) By establishing common in-memory and on-disk columnar standards, Arrow and Parquet enable more efficient data sharing and querying across systems without serialization overhead.
This document discusses Terraform, an open-source infrastructure as code tool. It begins by explaining how infrastructure can be defined and managed as code through services that have APIs. It then provides an overview of Terraform, including its core concepts of providers, resources, and data sources. The document demonstrates Terraform's declarative configuration syntax and process of planning and applying changes. It also covers features like modules, state management, data sources, and developing custom plugins.
22nd Athens Big Data Meetup - 1st Talk - MLOps Workshop: The Full ML Lifecycl...Athens Big Data
Title: MLOps Workshop: The Full ML Lifecycle - How to Use ML in Production
Speakers: Spyros Cavadias (https://www.linkedin.com/in/spyros-cavadias/), Konstantinos Pittas (https://www.linkedin.com/in/konstantinos-pittas-83310270/), Thanos Gkinakos (https://www.linkedin.com/in/thanos-gkinakos-03582a128/)
Date: Saturday, December 17, 2022
Event: https://www.meetup.com/athens-big-data/events/289927468/
Declarative & workflow based infrastructure with TerraformRadek Simko
Terraform allows users to define infrastructure as code to provision resources across multiple cloud platforms. It aims to describe infrastructure in a configuration file, provision resources efficiently by leveraging APIs, and manage the full lifecycle from creation to deletion. Key features include supporting composability across different infrastructure tiers, using a graph-based approach to parallelize operations for efficiency, and managing state to track resource unique IDs and allow recreating resources. Providers enable connectivity to different cloud APIs while resources define the specific infrastructure components and their properties.
OSDC 2015: Mitchell Hashimoto | Automating the Modern Datacenter, Development...NETWAYS
Physical, virtual, containers. Public cloud, private cloud, hybrid cloud. IaaS, PaaS, SaaS. These are the choices that we're faced with when architecting a datacenter of today. And the choice is not one or the other; it is often a combination of many of these. How do we remain in control of our datacenters? How do we deploy and configure software, manage change across disparate systems, and enforce policy/security? How do we do this in a way that operations engineers and developers alike can rejoice in the processes and workflow?
In this talk, I will discuss the problems faced by the modern datacenter, and how a set of open source tools including Vagrant, Packer, Consul, and Terraform can be used to tame the rising complexity curve and provide solutions for these problems.
This document provides an overview of Terraform, an open-source infrastructure as code tool. It discusses Terraform's goals of providing a unified view of infrastructure, composing multiple tiers of infrastructure from IaaS to PaaS to SaaS, and safely changing infrastructure over time with one workflow. Key features highlighted include being open source, using infrastructure as code, resource providers that interface with cloud APIs, and the plan and apply workflow. The document also covers topics like collaboration and version history in Terraform Enterprise, file examples, the plan and apply commands, resource providers, and new features in recent Terraform versions like destroy provisioners, remote backends, state locking, and state environments.
This document provides an overview and agenda for a presentation on Nomad, an open source cluster scheduler created by HashiCorp. The presentation will cover Nomad fundamentals including architecture, job configuration, and scheduling. It will also demonstrate Nomad's ability to schedule a million containers across thousands of hosts on Google Cloud Platform.
This document provides an overview and agenda for a presentation on Nomad, an open source cluster scheduler created by HashiCorp. The presentation covers Nomad fundamentals like architecture, job configuration, and scheduling. It also demonstrates Nomad's capabilities at large scale by describing a "million container challenge" deployment of 1 million containers across 1,000 jobs and 5,000 hosts on Google Cloud Platform. The document promotes an upcoming HashiConf conference for further discussion.
Atmosphere Conference 2015: Taming the Modern DatacenterPROIDEA
Speaker: Seth Vargo
Language: English
Today we are plagued by hundreds of choices when architecting a modern data center. Should our machines be virtual or physical? Should we use containers or Docker? Should we use a public cloud provider or a private cloud provider? Which configuration management tool is best to use? What about IaaS, PaaS, and SaaS? It would be manageable if these were binary choices; however, we often find ourselves in a hybrid environment.
As more operations choices are added to your data center, whether through company acquisitions, a growing development team, or general technical debt, managing complexity between legacy and new systems becomes a nightmare. Yet the end goal is still the same — safely deploy your application to your infrastructure. We need to tame our data centers by managing change across systems, enforcing policies, and by establishing a workflow for both developers and operations engineers to build in a collaborative environment.
This talk will discuss the problems faced in the modern data center, and how a set of innovative open source tooling can be used to tame the rising complexity curve. Join me on an adventure with Vagrant, Consul, and Terraform as we take your data center from chaos to control.
Visit our website: http://atmosphere-conference.com/
Aprovisionamiento multi-proveedor con Terraform - Plain Concepts DevOps dayPlain Concepts
La infraestructura como código (IaC) es una de las prácticas relacionadas con la cultura DevOps que está cogiendo más tracción en el desarrollo de software y Terraform es una de las herramientas más recomendadas para ello.
Se suele relacionar sobre todo con la creación de infraestructura en los grandes servicios “Cloud” -AWS, Azure, Google Cloud,…- pero es además algo aplicable a otros aspectos de IT como podrían ser la creación de usuarios en servicios de terceros o propios (Github, bases de datos,…), configuración de dominios (Dyn, GoDaddy,…), configuración de alertas (Grafana, OpsGenie)…
Durante esta sesión se explicará su funcionamiento básico y veremos en directo despliegues en varias de estas plataformas.
Erik Skytthe - Monitoring Mesos, Docker, Containers with Zabbix | ZabConf2016Zabbix
At DBC we are running docker and other container types in a mesos/marathon cluster environment. I will demonstrate how we collect statistics, logs etc. and monitor this environment, showing configuration examples, data flows and templates.
Some of the covered topics:
- Mesos master and agents
- Marathon Framework
- Docker engine
- Containers
- Zookeeper
- Elasticserach/ELK
Containerization helps us bundle dependencies with applications instead of having to use configuration management to prepare machines for running them, hence making build once run anywhere easy. For legacy applications this can be quite hard though when they spread persistent data across the file system.
In this talk I'll show how we can quickly set up a Go.CD server and agents for our Continuous Delivery pipelines on Google Cloud. The infrastructure creation is handled by Terraform, the server and agents are custom built Docker containers.
Burn down the silos! Helping dev and ops gel on high availability websitesLindsay Holmwood
HA websites are where the rubber meets the road - at 200km/h. Traditional separation of dev and ops just doesn't cut it.
Everything is related to everything. Code relies on performant and resilient infrastructure, but highly performant infrastructure will only get a poorly written application so far. Worse still, root cause analysis in HA sites will more often than not identify problems that don't clearly belong to either devs or ops.
The two options are collaborate or die.
This talk will introduce 3 core principles for improving collaboration between operations and development teams: consistency, repeatability, and visibility. These principles will be investigated with real world case studies and associated technologies audience members can start using now. In particular, there will be a focus on:
- fast provisioning of test environments with configuration management
- reliable and repeatable automated deployments
- application and infrastructure visibility with statistics collection, logging, and visualisation
A Hands-on Introduction on Terraform Best Concepts and Best Practices Nebulaworks
At our OC DevOps Meetup, we invited Rami Al-Ghami, a Sr. Software engineer at Workday to deliver a presentation on a Hands-On Terraform Best Concepts and Best Practices.
The software lifecycle does not end when the developer packages their code and makes it ready for deployment. The delivery of this code is an integral part of shipping a product. Infrastructure orchestration and resource configuration should follow a similar lifecycle (and process) to that of the software delivered on it. In this talk, Rami will discuss how to use Terraform to automate your infrastructure and software delivery.
MongoDB World 2019: Creating a Self-healing MongoDB Replica Set on GCP Comput...MongoDB
Take advantage of the elasticity of the cloud by creating resources that can heal themselves. Learn to create Compute Engine resources in GCP using Terraform that will install and configure a MongoDB replica set for you.
Infrastructure-as-code: bridging the gap between Devs and OpsMykyta Protsenko
Ops are overwhelmed with support. Devs are mad because their cannot deploy the changes as fast as they want. Sounds familiar?
Infrastructure-as-code can make your life easier by empowering developers and reducing operations' routine toil. It can cut down the lead time for infrastructure provisioning from hours or even days to minutes.
This talk reviews several IaC tools and approaches, showing how to integrate them into continuous delivery pipeline. It covers the problems and challenges that engineers may face while working with infrastructure-as-code tools and provides a few hands-on recipes to address them.
This document provides an overview of Terraform, an open-source tool for building, changing, and versioning infrastructure safely and efficiently. It discusses Terraform's core concepts including providers, resources, data sources, and modules. An example demonstrates creating AWS SQS and S3 resources and a Heroku app using Terraform configuration files. The document also covers Terraform's workflow, features like remote state and provisioning, and compares it to similar configuration management tools.
Deploying Plone and Volto, the Hard WayAsko Soukka
How about building Plone without buildout? Running Plone on Python 3 without WSGI? Deploying Plone and Volto with containers without Docker? Building all this in re-usable and safe manner in sandbox with restricted network access with Nix? Welcome to hear about our hipster setup where we lock, build and configure Plone deployments with Nix, insist to keep ZServer running on Python 3 for the love's sake, build software deployments into standalone tarball archives, and run them with Nomad – the simple on-premises-friendly alternative for K8S.
Vous avez récemment commencé à travailler sur Spark et vos jobs prennent une éternité pour se terminer ? Cette présentation est faite pour vous.
Himanshu Arora et Nitya Nand YADAV ont rassemblé de nombreuses bonnes pratiques, optimisations et ajustements qu'ils ont appliqué au fil des années en production pour rendre leurs jobs plus rapides et moins consommateurs de ressources.
Dans cette présentation, ils nous apprennent les techniques avancées d'optimisation de Spark, les formats de sérialisation des données, les formats de stockage, les optimisations hardware, contrôle sur la parallélisme, paramétrages de resource manager, meilleur data localité et l'optimisation du GC etc.
Ils nous font découvrir également l'utilisation appropriée de RDD, DataFrame et Dataset afin de bénéficier pleinement des optimisations internes apportées par Spark.
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MuCon 2019: Exploring Your Microservices Architecture Through Network Science...OpenCredo
Your microservice system has been up and running for a while. You know you’ve diligently employed every ounce of your experience and knowledge over time to design a sensible application architecture, with hopefully sensible boundaries. But time is now throwing new questions your way: Are my boundaries still sensible?
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Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
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5. Introduction to Apache Kafka and S3
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10. Configuring Camel K Integrations for Data Pipelines
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12. Jupyter Notebooks with Code Examples
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https://www.wask.co/ebooks/digital-marketing-trends-in-2024
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Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
53. ▸Manage environment separately
(separate state files per env)
▸Intuitive configuration
(reusable modules)
▸Reduced Duplicate Definitions further
(as DRY as possible given restrictions)
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