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Now days it is a challenge to monitor instances which are created/deleted on the fly (instances in auto scaling group for example), so how we could accomplish this with Icinga 2? Well, in this blog we will provide some hints, how to have such configuration without writing complicated AWS CLI/API calls or lambda functions, but configuring mainly icinga.

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Our passion at ITGix is programming and working with Cloud services and tools. With all the different sets of projects we have, our motivation and experience are inspired from technologies like Docker, Kubernetes, Icinga, Ansible, Chef, SaltStack, GitLab, Jenkins, AWS, Google Cloud and many more tools and services. Recently I got keen on Infrastructure as a Code and for the purpose we are using Terraform. Terraform is a somewhat versatile tool used for automating, codifying your Infrastructure and deploying resources around most of the major Cloud services providers. It uses a declarative language, developed by HashiCorp, called HCL (HashiCorp Configuration Language), which many people think that is a limited and not really innovative programming language. Personally, I cannot share the same opinion, however I can agree that setting conditional logic in Terraform can be a bit tricky and some certain types of tasks become very difficult without access to a full programming language.

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ITGix is proud to be named among the top outsourcing companies by Clutch, ratings and review platform based in Washington DC. We were considered for this honor because of our service offerings in cloud consulting, managed services, and IT strategy consulting. The shortlist was a part of Clutch’s Global Awards which recognizes the top service providers in the B2B field.Our rating was determined primarily by our ability to deliver quality services from to our clients. Analysts at Clutch interviewed some of our partners to learn more about the projects we have helped them out with and their experience with us. We are proud to have received a 5-star review. Below is an expert: “We recently had a disaster on one of our cloud platforms, and we were able to resume service using ITGix’s disaster recovery site. They’re a solid company that our employees enjoy interacting with... They’re responsive and timely. Because of the nature of the work, we share a large amount of documentation, and they keep it organized and accessible. We communicate via email.”  We are very proud of our accomplishment. We encourage you to read the complete review on our profile and reach out to us if you wanted to learn more about our IT services! 

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We’ve been contacted to conduct a tuning for performance for a huge AWS environment. It is used to host the server side of a mobile application for a TV show that gives the ability to its viewers to vote on various questions during the show. Since the show is scheduled only once per week, it’s a perfect use case for a cloud on-demand environment, that is only being raised during the show, then after it ends, all VMS are shutdown or destroyed. In this way costs are cut to the their minimum, no need to keep expensive private physical servers at all times in a private data center for this.  You can imagine the load from the full set of viewers who are most of the times between 200 000 and 300 000 and they need to vote in parallel during one minute for a certain question. This could be a serious challenge for the system.

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The icinga2 configuration options are rich and provide you with a lot of ways to re-use what you already have. They serve well, but once your monitoring becomes big enough they just don't cut it anymore. Reducing the load on the monitoring hosts and the servers you check becomes a high priority. One way to solve this is to use the API and create passive services where applicable. At the time of writing this blog there isn't enough information for people who are trying to learn what passive checks are and how to implement them. I'm writing this with hope that I will make it easier for people who want to know how to get started. Passive Checks Icinga API Automation and autodiscovery Performance Data

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    This is a first post of a mini-series dedicated to running Kubernetes hosted on AWS. First post will be about the considerations we have made when proposing production ready and Enterprise grade Kubernetes environment to our clients. I will go more technical, with the tools and AWS services we are using, in the next blog post, here I will try to cover what problems we are solving.     High availability is a characteristic we want our system to have. We aim to ensure an agreed level of operational performance (uptime) for a higher than normal period. These are the principles we follow when doing the system design:  - Elimination of single points of failure. This means adding redundancy to the system so that failure of a component does not mean failure of the entire system.  - Reliable crossover. In redundant systems, the crossover point itself tends to become a single point of failure. Reliable systems must provide for reliable crossover.  - Detection of failures as they occur. If the two principles above are observed, then a user may never see a failure. But the maintenance activity must.        Below graph shows the Kubernetes Master components used for setting up a cluster. Will go thorough them one by one :

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  Message Oriented Middleware (MOM) MOM is а connectivity software that consists of a set of services that allow multiple applications running on one or more machines to interact across a network. Message queuing applications use asynchronous processing to send and receive messages. They read and operate on the messages independently. In its simplest form a message sent from an application to another application will look like something like this : There are many implementations of this functionality, some are Open Source and some are proprietary. A few examples are IBM MQSeries, Apache ActiveMQ, RabbitM, Kafka, etc. In this article we will go in more detail about IBM MQ since it is the most widely adopted implementation in the Enterprise.

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This tutorial explains how to set-up the check_oracle_health script (credits to Gerhard Lausser) to work on your Nagios environment on CentOS (or any RedHat based Linux). This nagios plugin allows to monitor many oracle DB parameters – like tablespaces size, session, process count, SGA pool etc. Check it out on the author’s webset.The hardest part of the setup is installing the dependent perl libraries and making modifications in the perl code for them to work.On oracle server we need to create the monitoring user and grant rights, only the minimum necessary for the script to work.

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What is the purpose of a tool like SaltStack and a better question, what problem does it solve ?The two main purposes of SaltStack are configuration management and remote execution. You have probably heard or used one of the more popular alternatives of SaltStack - Ansible, Puppet, or Chef. All of them pretty much accomplish the same goal. I like Salt in particular because it is written in Python and it is relatively lightweight. It uses ZeroMQ's communication layer which makes it really fast and it also uses the PyYAML for its configuration management recipes (called states). In a nutshell if you manage any number of servers and you need to do something on them, you would have to log in to each one at a time and do your task. Even if that task is a small one like restarting an instance or checking their uptime, or a larger one like doing an installation and configuration of something, you would still have to do it one server at a time. If you manage a lot of servers you will need to do a lot of manual work to accomplish your tasks. This is where Salt Stack can be applied to automate your work and provide the ability to remotely execute commands on any number of machines. Salt works using either Master/Minion setup where you have a master node from which you execute commands to the minion nodes, or using salt-ssh which is pretty much what it sounds like, it allows you to execute anything that you normally would to a configured minion on any machine over ssh, no matter if Salt is installed there.

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Since you are here, you have probably heard of Docker. When you search it in Google the first result is: "Docker - Build, Ship, and Run Any App, Anywhere" - don't believe me, try it yourself. That sounds great but in the means of Privacy and protecting your intellectual  property, it doesn't. This is because of the question "Ship to where ?", to Docker hub where the whole world can just do a simple pull and have all your work at his disposal? In this blog post I will introduce you to the Docker Trusted Registry and its benefits. It is a registry service that you can run on-premise or in virtual private cloud, where it is safe behind your company firewall. From here it is easy to store and manage your Docker images, which are the building blocks of your application stack. Trusted Registry is available in conjunction with a commercially supported Docker Engine to provide you with the peace of mind and support needed for your application environment. It is part of the Docker Datacenter Subscription which also includes a Universal Control Panel. The Docker Trusted registry is easy to install  and integrate with your existing infrastructure.

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VPN, or Virtual Private Network, allows you to create a secure connection to another network over the Internet which can be very beneficial for some use cases. VPNs can be used for many things, for example - access region-restricted websites, shield your browsing activity from bad guys on public Wi-Fi, connect and use local resources which are inaccessible from the outside world or simply create a secure network between your servers and isolate them. So, what are the common steps for creating a VPN. You need to first connect to the public internet through the ISP (Internet Service Provider), then initiate a VPN using a client software. Sounds easy, right? Well it depends on the software you choose, whereby most of the VPN solutions follow the client-server principle. That means, all nodes connect to e central server which is the central point to all others. By such environment, the whole traffic passes through the central server creating a star topology, so this server needs lots of bandwidth. In case that the central server fails and it’s not able to handle the whole traffic, the VPN will go down and the other members will not be able to communicate. This is the main disadvantage by such setting. So, if you don’t want to have that single point of failure, you can use a full mesh topology, where every participant talk to the others without having a central server. If one of them fails, the other members will not be affected. A good, simple and reliable peer-to-peer/full mesh solution is the PeerVPN.

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           Icinga2 is a great tool built upon the foundation of the well known Nagios monitoring, inheriting all the pros it has to offer. With many plugins available in your repository and thousands more in the community-driven Nagios-exchange website, icinga2 is a very good choice for your infrastructure monitoring. I will cover some of the optional features that can be tweaked to suit your needs, once the main configuration has been set up. Some of the points are: Taking full advantage of variables defined in your Host file. Setting up custom scheduled downtimes. Changing the timeout for specific checks. Using a different user for your checks. Writing your own plugin.

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In addition to the article about the PeerVPN installation and configuration, I will now show you more advanced and quite ‘modern’ way to provision several servers and get your VPN client up really fast. You’ve probably heard of Ansible already. Well, one of its use cases is exactly what we need here: Configuration Manager. Many of us have experienced The Headache, when you need to install, configure and then administer a whole environment. Yes, to repeat the same steps on hundreds of servers, where you have different OS distributions, application versions and all kind of dependencies, and all of that certainly lead to some problems.Well, Ansible is here to help you with all that stuff. You can choose, set and customize anything that is required for specific environment and suit its needs. So, let us start with the introduction to ansible, its structure and components.In my opinion there are two approaches when you first start with Ansible. The first one is to read the official introduction to Ansible, which explains a lot about its structure and then start with simple playbook which you then extend to a role. Or the second one, where you make use of the Ansible Galaxy, which has a lot of community-provided roles open for use. Well not every role is that much scalable and flexible as you want so you can simply combine both approaches, take an already built role and expand its functionalities. If you learn that quick and all of that is boring, you can start building your own Ansible modules.

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The rule of the "cloud" has already been established and now we have multiple vendors fighting for market share. Many companies started relying on the cloud and seeking more and more automation and could services. It looks easy, you just select a cloud provider, use it's services and you have several virtual machines or containers within minutes. Sounds like magic? Well, Here is the question you are probably asking yourself . What is behind it all? The answer is;  good old virtualization, strong APIs and scripting.   I guess most of you, who are to some extent already familiar with vitualization, and have the affinity to work with opensource technologies have used Xen. It was the very first in the opensource world, and that is for sure. Its first release was in 2002 and it definitely became one of the dominant virtualization solutions in the opensource world. If we take a look at the main vendors like Oracle for example, we will see that behind OVM is again Xen. At the same time lots of companies started using another solution, which you might have heard of - Citrix. The company that created it became very well known.  

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I'm not a big NFS fan ever since I worked as a Linux/Unix administrator way back in the good old days. Sometimes when the NFS server hung, lost network connectivity or something else happened all clients that had mounts from the NFS completely blocked waiting for it to come back up, because it is so deep in the kernel. Аll commands, even "ls", froze and the only cure was forcibly rebooting them to get them back online. Neat, eh?When NFS v4.1 emerged, back in 2010 hopes were that it will fix everything. I was a bit sceptical but decided to give it a shot and true, many new fixes in the protocol and implementation were made that enhanced the stability. Some of them were: blocking locks that allow client to ping the server if the lock is released, not only wait for notifications, timeout for server unavailable, parallel access. From what I saw, I couldn’t really break it beyond repair.As time went by Openstack offered the option to have NFS as a storage backend. We decided to use it for one deployment where we saw this technology as appropriate, because we didn't need highly available storage with replication that occupies twice the space, but we needed Cinder volumes to get mounted across the hypervisors. I had a feeling that something could go wrong while making the installation, because I remembered all those nights rebooting servers from ILo / IMPI.

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Backup is an essential part of the IT infrastructure management. Having HA solutions, RAIDs etc. doesn't free you from the need of backup. In case of a human error all those techniques will not save you, only the backup will. However as the saying goes "Your backups are only as good as your restores", so we have to think about regularly checking our backups for consistency.In Openstack it's highly recommended to use Cinder as the main storage provider. Cinder gives you the possibility to create block volumes and attach them to your virtual machines. The best practice is that you keep all your application data onto volumes and not on the instance disk, this disk should be used for the operation system files only, that come from the OS image ( of course packages installed from repositories will also go there) . In this article we will show you more reasons to do so.What you would typically want from a good backup solution is: online backup possibility, easy restores, consistency, easy management, to use as less space as possible.Although it's possible to have a traditional backup solution installed on every virtual machine, Openstack offers us other options to backup our data using snapshotting. The downside is that you can't have an "incremental" snapshot copy yet, you have to store the full size of your snapshots every time you backup. However the simplicity of backups and more importantly restores is far greater than supporting a "in-VM" backup solution that supports incremental backups. 

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In my previous blogpost I was discussing how to monitor RabbitMQ as a centralized message Q of Openstack. Well, that's quite important but the end goal of having cloud are the instance on top of the machine. Most of you and especially the infrastructure guys who dig into monitoring will know what are the most important components to look over.The reason to monitor is to have reasonable planning which is probably the drill in cloud environment where you have spawnlarge number of virtual machines of containers. On the other hand having the data in one glance is very easy to increase the reliability, uptime plan better your architecture and identify the bottlenecks of your setup.

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Last year we focused on the Openstack technology and the projects behind it. We decided to stress on it and move our scope in that direction because of the rich features and flexibility that it provides. But as we know great power comes with great responsibility.

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If you're an administrator of virtualized environments you have definetly ran into IO performance issues. IO is the first bottleneck that one hits. Luckily persistant storage has evolved troughout the years and lately we see the high performant SSDs at a reasonable price, still far higher to allow organizations to fully migrate to SSD. The hybrid environments become more and more popular as they combine the low costs for traditional HDD with the high performant Solid state drives. One of the key features of the Cinder storage back- end component of Openstack is the flexibility that allows us to have more than one storage backend on our storage node. This gives us the flexibility to diferentiate the IO heavy applications from the more compute-oriented ones that are more heavy on cpu usage. Typical example is to configure a database VM to run from a SSD drive and the application server cluster to be on a normal storage that is heavily read only during startup. Here is how to achive that with OpenStack and Cinder.

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INTRODUCTION TO DOCKER If you have been following the “cloud” trends you probably have heard of Docker. It is an open source implementation of the LXC (Linux Containers) used for packaging an application and its needed dependencies into a container that can be deployed and replaced easily. The containerization in Docker is achieved via resource isolation (cgroups), kernel names spaces (isolating the application’s view of the OS, process trees, etc) and a union-capable file system (such as aufs – mounting multiple directories into one that appears to contain their combined contents). Using containers removes the overhead of having to create, deploy and maintain full VMs for running your applications. As well as providing completely identical PROD, Staging, QA, DEV environments. In some cases you can even move a container from one server to another, making it ideal to spin a quick instance of your PROD environment on a separate server to do a quick test without messing with the actual PROD environment.

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ITGix is proud to announce the start of our innovative DevOps Platform. It aims to enable companies integrate latest DevOps practices in their environments, while keeping everything in well organized and automated manner.

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JVM Heap spacePossible failures of java code core dump JVM Tuning the application server is recommended as opposed to just sticking with the default values assigned during an application server install. If the heap size is not managed or tuned, you may see the symptoms of poor memory management which can vary from intermittent performance problems to the periodic failure and automatic restarts of the JVM which may not generate a core dump or error.

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