— ROELBOB
Tag: automation
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Rackn Extends Reach of IT-as-Code Framework
Rackn announced the Digital Rebar platform it created to automate the provisioning of bare-metal infrastructure now can be applied simultaneously across multiple physical sites.
Company CEO Rob Hirschfeld said Digital Rebar 4.3 makes it possible to manage IT infrastructure as code across highly distributed computing environments. Previously, IT organizations would have needed additional versions of Digital Rebar for each physical data center.
Hirschfeld also noted IT teams can also set up mirrors of data centers, now that Digital Rebar can be employed across multiple sites.
IT teams that adopt Digital Rebar can define workflows through which, for example, instances of virtual machines or Kubernetes can automatically be deployed on hundreds of thousands of servers in about an hour, said Hirschfeld.
Accomplishing that same task using manual processes would take most IT teams six months, he noted, adding IT teams can even use Digital Rebar to deploy instances Kubernetes on virtual machines at scale.
Hirschfeld noted many IT teams assume they need to have a layer of virtualization in place before they can start automating the management of their IT environment. Digital Rebar provides a framework around a common set of application programming interfaces (APIs) through which servers, storage and networking resources can be provisioned consistently. In addition, IT teams can set up a to manage IT infrastructure on an ongoing basis, including firmware and operating system updates and cluster configurations.
Digital Rebar doesn’t necessarily replace the need for frameworks such as OpenStack or VMware vSphere. However, it does provide a simpler mechanism for installing them. Alternatively, IT teams can employ Digital Rebar to deploy software such as Kubernetes on a bare-metal server.
Hirschfeld said Digital Rebar is designed to be deployed on-premises or in a public cloud rather than be accessed as a software-as-a-service (SaaS) application. That approach means IT teams operating in highly regulated industries can still take advantage of the framework, he said.
While the concept of IT as code has been around for a while, IT teams that are being asked to now manage IT at an unprecedented scale are turning to IT automation frameworks in larger numbers. Hirschfeld said Digital Rebar is now designed to replace other frameworks as much as it is to provide a complementary framework for specifically managing bare-metal infrastructure. In fact, Digital Rebar can be access vis Terraform or Ansible using a plug-in that Rackn makes available.
Rackn also plans to extend the reach of Digital Rebar out to edge computing platforms as well as endpoints based on, for example, Raspberry Pi platforms, he added.
Most IT teams will eventually wind up employing multiple IT automation frameworks in place of thousands of custom scripts that many IT professionals have developed themselves. The issue with most of those scripts is they don’t tend to scale especially well. In addition, they are usually poorly documented so when the author of the script leaves the organization the remaining IT staff wind up having to write another custom script because no one is quite sure how the script in place works. Whatever the path forward, the one thing that is certain is the days of being able to get by manually provisioning platforms is finally coming to a merciful end.
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Cohesity, HPE, Cisco Create ROBO Platform
Cohesity, in tandem with Hewlett-Packard Enterprise (HPE) and Cisco Systems, today announced an integrated server and storage platform for remote office/branch offices (ROBOs) designed to be installed in a turnkey fashion.
Rather than requiring IT staff to be present in a ROBO, the platforms are designed to be installed by a local office manager and then centrally managed using the Helios management platform developed by Cohesity. IT organizations will have the choice of configuring those platforms with servers from either HPE or Cisco. The platforms themselves can be ordered only directly from either HPE or Cisco. HPE is also an investor in Cohesity.
Raj Dutt, director of product marketing for Cohesity, said the ROBO platforms being offered in collaboration with both companies is an extension of a capability Cohesity already has that allows its distributed file system to be deployed on virtual machines. The ROBO platforms, which replace the need to manage local instances of Windows file servers, extend that capability to a set of turnkey physical appliances that can be managed either via APIs provided by Cohesity or through the graphical user interface (GUI) the company makes available as part of Helios, said Dutt.
At the core of the ROBO platforms is a multiprotocol storage system capable of storing files locally or accessing data stored in object-based storage systems that support the S3 application programming interface (API) defined by Amazon Web Services (AWS). Cohesity claims this is the first platform to combine file and object services with backup and recovery and archival services in the cloud in a turnkey platform designed specifically for ROBO environments. That capability also enables Cohesity to store an immutable copy of data that can be recovered in the event of a ransomware attack, noted Dutt.
Dutt, citing data from Enterprise Strategy Group (ESG), said more than half of enterprise data will be created and processed outside the data center or a public cloud by 2022. Much of that data will be created and processed in real-time on a wide variety of edge computing platforms. The goal now is to reduce the amount of data any edge computing platform needs to access over a wide area network (WAN), he said. The Cohesity platform also employs global variable-length sliding window deduplication and compression to optimize both storage efficiency and bandwidth utilization. All data at rest and in-flight is also encrypted.
It’s unclear to what degree organizations will be modernizing the management of IT in ROBO environments. What is clear is the need to have local IT administrators or dispatch IT teams to set up systems in ROBO environments is coming to an end, as IT infrastructure deployments and ongoing management become more automated. In the event of platform failure, it would even be less expensive to simply make a second appliance available locally or use an overnight delivery service to send a replacement. Of course, that may mean fewer road trips for the IT staff. However, most IT organizations have plenty of other tasks in the data center to keep most of their IT staff fully engaged.
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5G Security: Mitigating Threats in the Era of Hyperspeed and Hyperconnectivity
5G is one of the hottest industry buzzwords right now, and for good reason. Beyond its ability to deliver massive capacity, it is expected to be one of the fastest and most pervasive technologies of all time, fundamentally changing every sector of the economy.
In recent years, we’ve lived through 3G and 4G. So what makes this next generation so revolutionary? Put simply, every emerging technology we are collectively excited about—IoT, VR/AR gaming, autonomous cars and smart cities—is enabled through 5G. This is because this next generation of the mobile network will increase the speed of service by extending high bandwidth and connectivity to the edge, a possibility that wasn’t quite there with 4G. 5G will connect everything around us via a network that is 100x faster than our current cellular connection and 10x faster than home broadband service.
The technology is ready. From a commercial and business perspective, however, 5G implementation is still in its infancy. When it comes to capitalizing on the many use cases 5G offers, what is the holdup? With faster speeds, enormous data capacity, lower latency and more devices connecting and communicating than ever before, the security vulnerabilities are extreme. Given we are in the early stages of 5G deployments, service providers do not even know the full extent of the security concerns; they are just planning for the number of devices joining the network to grow exponentially. With the proliferation of connected personal devices, data privacy concerns have never been higher.
To understand the potentially detrimental threats to personal safety and data privacy, we must first look at specific use cases enabled through this technology.
The 5G Effect
5G is more than just faster speeds—it is unlocking some of the most highly sought-after technologies of the decade. This is because low latency, or next-to-nothing lag time, allows a device asking something of the network to get a response almost instantaneously. For VR and AR gaming applications, this means a seamless user experience. And while sensory video games are good fun, these same principles can carry over to more serious applications in hospitals and other medical settings: By using a VR headset and special glove to control a robot arm, for example, a surgeon may have the ability to operate on a patient offsite.
This extreme scenario offers two major risks: network lags and hacked equipment. An IoT-enabled hospital may have tens of thousands of “things” that could be compromised. Emergency room devices cannot afford to be starved for bandwidth if an admin printer is clogging the network. Any glitch in the network may lead to a slight delay in action, resulting in dangerous consequences. Additionally, with nefarious entries into the network through the high volume of vulnerable endpoints, the attack may have dire repercussions.
A hospital is just one high-stakes environment. Now consider the IoT devices connected to a 5G network operating all around us—autonomous cars, energy grids, home security systems, etc.—the smallest glitch or endpoint vulnerability could lead to life-threatening situations.
Many people do not realize 5G and IoT will have a major effect on seemingly innocuous devices such as refrigerators, thermometers and even light bulbs. While 5G will enable users to check on these types of appliances remotely through a simple app, convenience comes with consequence as these devices can also be usurped by malicious characters. It is important to recognize what 5G can enable, but also how it will all come together.
Preparing for the Next-Gen
Here are some tips on how enterprises can develop an effective 5G-ready security posture that encompasses the entire network:
Invest in automation: 5G security poses its own Catch-22; because connections happen faster, attacks and breaches also happen faster and potentially with much more reach. To mitigate threats, 5G security will require actionable insights at scale. To achieve this, organizations need security systems that detect and automatically enforce security policy from endpoints to edge and every cloud in between.
Scale up and out: To avoid a massive bottleneck, a proper 5G security posture will require upgrades to both physical and virtual infrastructures. Developing a secure architecture and solution that can keep up with the pace and scale of 5G without slowing it down is a large, but necessary, undertaking. The trick is to build in machine learning capabilities so the network can get smarter. Malware must traverse the network, so why not use all the data that the network already produces to fight it? A network that is constantly learning and updating is the only way to operate in the 5G landscape.
Be proactive: History has shown us that whenever we expand our computing power and connectivity capabilities, we also expand the threat landscape. Not only that but as we continue to increase our dependency on communications networks and technologies to move tremendous amounts of data, there is greater potential for serious disaster should they be compromised. This is not the time to sit back and watch how things unfold, as major security risks are on the line.
The use cases for 5G are plentiful. If we can conquer the threats, we can conquer anything the technology enables us to do—and the possibilities are endless.
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Automation Hacks for DevOps Teams
DevOps teams are expected to do more work in less time. They need to plan, test, build, secure and release applications at a fast-paced rate. Of course, the DevOps team needs to achieve all of this while maintaining high software quality. This is why automation is a crucial part of the DevOps workflow. The goal is to delegate repetitive tasks to the machine, and free up dev time for more complex jobs.
Below are some helpful automation hacks you can apply to boost the effectiveness of your DevOps practices.
Automating Regulatory Compliance
Properly managing regulatory compliance is vital for many organizations to avoid fines and operate legally. Although compliance standards vary by industry, most focus on ensuring privacy and confidentiality. To meet these standards, companies must secure data and prove they are taking the appropriate measures. This proof is commonly accomplished with the maintenance of a clear digital trail.
You can use DevOps automation to log and store digital access trails for your protected data. You can also use automated testing and deployment to ensure that only code that passes compliance tests is deployed. This prevents compliance issues from being pushed to production and helps keep your data secure.
Automating Development Environments
DevOps workflows require frequent creation and elimination of environments, for testing, deployment and development. These environments can be created manually but it is more efficient to create environments automatically. This can be done using a golden image with your required configurations.
Using standardized base images ensures that you are working with consistent environments and standardizes configurations and privileges. These images can be used for local or remote machines and can be initialized automatically.
There are a variety of tools you can use to create and automate environment creation. Chef and Vagrant are two of the most popular. Both of these tools offer an accessible API and enable you to script automation using common languages and syntax.
Automating Code Review
Code review is an essential part of DevOps processes but it is also one of the lengthier and more tedious processes. Automation can help you perform this process more efficiently. Automatic code review works similarly to manual review except it is done using tools that integrate with development environments. These tools can check for styling, security, duplication, complexity and code coverage, and can auto-suggest corrections. Some popular tools for this automation include Codebeat, Code climate and Codacy.
Automating File Synchronization and File Uploads
Many DevOps and development teams use the public cloud for quickly spinning up development and test environments. However, what happens when the production environment, or other critical resources used in the dev/test process, are deployed on-premises? Having a fast, automated and reliable way to synchronize files between the on-premise data center and the cloud can save time and headaches.
There are a few approaches to synchronize files:
- Scripting file uploads and downloads. The most basic method is to use shell scripts and FTP or SFTP to upload and download files between local and cloud environments. However, this can be fragile, unreliable and difficult to scale.
- Using APIs of cloud storage services. You can move data to and from the cloud using cloud storage APIs, such as the Amazon S3 API, the Box API or specialized hosting services such as Cloudinary.
- Hybrid cloud. The ultimate solution is to create a hybrid cloud architecture where applications, developers and users view the local environment and the public cloud as one unit, and data is synchronized transparently in the background.
Collaboration Tools for DevOps Teams
There are a number of collaborative tools that teams can use to further boost gains from automation. These tools can help bridge gaps in automation and processes and ensure smooth workflows.
Slack: a chat tool that DevOps teams can integrate with automation tooling. It includes features for segregating discussions by topic, team or purpose; uploading shared files and documents; and initiating or receiving alerts from automated processes via integrations.
Jira: a tool that enables you to create and assign tasks. It includes features for scrum and kanban methodologies, unified reporting and backlog tracking. You can integrate it with many common DevOps tools, such as Jenkins.
Trello: a cloud-based Kanban board tool. It enables you to create project boards that can be shared across teams to track project progress. Through integrations, you can automate the updating of cards or initiate processes when cards are manually moved.
Asana: another cloud-based Kanban tool. Like Trello, it enables you to track and collaborate on projects across a team. Typically, when teams use tools such as Asana, they create multiple boards for different project aspects. These boards can then be viewed individually or from a central dashboard.
Conclusion
Hopefully, this article helped you figure out how to leverage automation for improved efficiency. There are many automation options for DevOps, including automated regulatory compliance, automated infrastructure, automated code review and automated file synchronization.
For DevOps project management, you can use collaboration tools such as Slack, Jira, Trello and Asana. Remember to make sure that any tool you introduce can be simply and easily integrated into your current environment. The tools of your choice also need to fit the skillset of all collaborators. For ease of use, keep your tooling ecosystem simple and minimalistic.
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Never Ignore the E-Factor
When cloud burst upon the scene, we were treated to wild-eyed prognosticators telling us about the death of the traditional data center. This is a trend in IT that you would think we’d learn from, but we repeat every couple of years. 4GLs, no, XML, no…Were all going to end development, and yet here we are, with more lines of code and more programming languages in use. It just keeps happening.
These all share two common failings. First, technology in use today may not be perfect, but it is getting the job done, so dumping it for the new silver bullet is an unlikely result either in the long or the short term. For example, we’re many iterations beyond the conception of the C programming language, and yet for some purposes it is still going strong–because it does the job.
But that’s a little tangential to today’s discussion. Today, the other failing is where I’d like to focus. The E-Factor.
Enterprises are a lot of things, but one of the things the successful ones are not is careless. Cloud use in the enterprise was always going to be both multi-cloud and hybrid. Why? Multi-cloud because sole supplier arrangements are riddled with possible issues, and hybrid because every enterprise has something they want to maintain sole control of or something that simply can’t be moved but they want to push toward newer environments.
We were always going to have multiple choices, and successful enterprises were always going to use multiple of them. Containers facilitate this truth a lot. The ability to run containers pretty much anywhere makes them portable, as long as staff is familiar with the infrastructure of a given environment so they can support the container management system in that environment. But even without containers, a cloud portability solution was inevitable.
There is a massive amount of automation going into IT right now, all for the good. Freeing up traditionally scarce IT hours to focus on more and better services is all to the positive. Inevitably, one or more of these automation tools will be hailed as “The End of X.” Ignore them, and keep rocking at your job. AIOps seems most likely to gather this type of following right now. It will offer a flood of new data and consolidated views of that data, but not much else in the near term. Even when decisions start to be automated, full-on automation based upon AIOps feedback still needs code to run against and infrastructure to run on, so no doom and gloom there.
Apply the E-Factor to anything hailed as a silver bullet. If you’ve worked in the enterprise, you know there are so many variables in the datacenter that any silver bullet would have to be a splintering round, each splinter behaving in a completely different manner to address current IT needs. More options are always good, and I, for one, go after new tech because I’m non-stop curious. But it is indeed just more options for your IT needs. Use the ones that will help, ditch the ones that make things worse and ignore the cheering “This time we mean it!” crowd.
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Three Keys to Successful AI Adoption
Over the past several years, we have begun to see the emergence of artificial intelligence (AI) in businesses. According to a study for the AI Index 2019 Annual Report, more than half of respondents report their companies are using AI in at least one function or business unit. Thirty percent report they have AI embedded across multiple areas of their business. As businesses continue to develop their understanding of what is possible with AI, we can expect to see a continued increase in AI adoption.
People used to say “software is eating the world.” Moving forward, people will be saying “AI is eating the software world.” You can expect to see standard enterprise and cloud software programs become indistinguishable from AI. Currently, the success rates of AI projects fall well short of what we see in enterprise software success rates. A 2019 study by Pactera found that 85% of AI projects fail to deliver on their intended promises. As software and AI bind together, expect to see a dramatic increase in the success rate of these AI projects. AI adoption will begin to align more with traditional success rates associated with enterprise software as a category.
As software and AI begin to merge together and enterprises look to invest in AI, there are a few keys to success.
Increase Your Organizational IQ with AI
Human factors are public enemy number one as it relates to AI adoption. For companies wanting to invest in AI, it starts with education. Companies need to become better educated on the options available to them through AI. We need to move away from viewing AI as a black box where magic happens. Through better education, the average business consumer will be able to understand the various disciplines of AI, such as natural language processing, vision, unsupervised learning and machine learning. As companies increase their IQ relative to AI, businesses will begin to understand the difficulty of AI projects. While this will create short term challenges, it ultimately will help the success of AI adoption in the future.
Commit to a Journey with Frequent Recalibration
Enterprises must move beyond merely being educated about AI in order to remain competitive. Business leaders will have to step past the exploratory and proof of concept phases and begin delivering real value to the business. This will mean the continuous delivery of intelligent solutions across several areas of the business. AI is not like traditional software projects where you measure twice and cut once, deploy and then observe for several months. It is a continuous journey of discovery that will require consistent adjustments. AI is different and requires you to make changes to existing predictive models based on your real-time findings.
If the Insight Is Not Actionable, It Doesn’t Matter
We have already seen AI become more and more embedded into analytics solutions and this is only going to continue. The convergence of AI and analytics is crucial to the success of AI projects. Over the past 20 years, analytical reporting has been provided to all users. With the addition of AI, machine learning models become analysis engines providing prescriptive actions to business users rather than the business uses having to interpret the analytics themselves. Again, this is a huge component in the success of AI adoption. It will not be enough for businesses to gain insights from their AI investment, success will be measured on what they do with those insights. Leveraging the insights from AI starts by providing actions directly to the users that can act on them within their existing workflow.
The power of AI is still largely untapped. It is already creating a massive shift in how we work and that is only the beginning. For those who have worked in IT and software, you need to adopt a whole new approach to AI projects. In the AI world, data is the driving force rather than a necessary evil. The emerging technology will require professionals to expand their skill sets beyond the traditional technical skills and into the disciplines of math and statistics. By doing so, we can expect to see a massive increase in successful AI adoption.
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SIOS Technology Automates Rebooting of AWS EC2 VM Instances
SIOS Technology Corp. this week launched SIOS AppKeeper, a tool that automatically reboots instances of EC2 virtual machines anytime they fail.
Michael Bilancieri, senior vice president of products and marketing for SIOS, said SIOS AppKeeper is an extension of the work SIOS has historically done to enable servers and clusters to failover. However, many organizations don’t require that level of availability, so SIOS developed AppKeeper to provide a way to automate the process of restarting virtual machines in the cloud, said Bilancieri.
SIOS AppKeeper also provides a dashboard through which DevOps teams can centrally manage the stream of alerts that are generated when there is an EC2 issue, he said. SIOS AppKeeper is a software-as-a-service (SaaS) application so there is no software to be installed. Instead, organizations log into their AWS account and select which instances and services to monitor and the level of protection they want SIOS AppKeeper to provide.
Pricing for SIOS AppKeeper starts at $40 per EC2 instance. Monitoring and alert capabilities are provided by default. Restart services, reboot instances and reboot instances only if a restart of services fails are all options. Organizations can opt to access SIOS AppKeeper either via the graphical user interface provided or via an application programming interface (API), Bilanieri said.
Previously, SIOS AppKeeper was only available in Japan. Based on data from those customers, the average customer with only three AWS EC2 instances experienced downtime at least once a month. With SIOS AppKeeper, customers were able to reduce downtime by 90%, Bilancieri noted.
SIOS will consider adding support for other public clouds based on customer demand, he said.
Cloud service providers, in keeping with the “pets versus cattle” ethos, tend to view virtual machines as being disposable. However, whenever there is an issue someone on the IT team still needs to take the time to restart a virtual machine, Bilancieri said.
Despite the drive to ruthlessly automate in the management of IT in the age of DevOps, there are still many tasks being performed manually. As the number of workloads in cloud computing environments continue to increase, those tasks conspire to slow IT operations. There are, of course, many ways to automate IT processes in the cloud. SIOS is making a case for a simpler approach to managing EC2 instances that doesn’t require IT teams to set up an entire IT automation framework.
Many IT teams will opt to create their own scripts to manage EC2 instances. However, it’s all too often the case that those scripts are poorly documented and don’t scale especially well over time. In addition, each time the IT professional who wrote a script that the organization depends on leaves the organization, there is no one left to update and maintain the script and new members of the IT team wind up writing yet another script to perform the same function.
There will always be some type of script floating around the IT environment. However, in the age of DevOps, the time to start reducing the number of those scripts that need to be supported might be at hand.
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Latest Chef Habitat Release Embraces On-Premises IT
Chef today announced that the Chef Habitat automation framework for building and deploying applications can now be used in on-premises IT environments.
Mike Krasnow, a senior product manager for Chef, said version 1.5 of Habitat makes it possible to now store applications packages and their dependencies locally in addition to the cloud. In addition, pre-built application packages and dependencies from the Builder service can be deployed across multiple on-premises instances.
An Applications tab in Chef Automate now shows the service groups and instances that are deployed to make it easier to understand what’s deployed where and the health of each service. Both the Habitat Builder installer and the application dashboard are integrated with Chef Automate, which uses the same installer as Chef Habitat.
Finally, the Habitat Supervisor module is now more stable, easier to configure and manage, and provides improved support for Windows applications.
Krasnow said Chef has seen a 300% increase in the use of the software-as-a-service (SaaS) instance of Chef Habitat in the last year. Organizations that have embraced Chef Habitat include Alaska Airlines, Rakuten, and Walmart. That rate of adoption should increase now that an on-premises edition is available, he said, including among IT organizations in highly regulated industries that are not allowed to employ cloud services. In fact, at least 70% of all application workloads are still deployed in on-premises IT environments.
Chef Habitat appeals most to organizations that have embraced best DevOps practices to programmatically deploy applications, said Krasnow. There are rival automation platforms that make use of declarative approaches to automation that appeal more to IT generalists. However, he noted, organizations that want to empower DevOps teams tend to prefer a more programmatic approach.
For more than a decade now Chef has been driving adoption of IT automation. However, it’s only relatively recently that organizations have been employing IT automation at scale as part of their efforts to embrace best DevOps practices. As interest in IT automation frameworks has risen, so too has the number of options. Some organizations are even employing multiple IT automation frameworks within different business units. They may one day standardize on a single IT automation framework, but many DevOps teams will simply opt to employ the IT automation framework the members of their team already know. If the members of that team in charge of IT operations don’t have a lot of programming expertise, chances are high they will opt for a more declarative approach. DevOps teams that have developers who deploy applications on their own are likely to prefer a more programmatic approach.
Regardless of the platform chosen, it’s clear the days of manually deploying applications using custom scripts are coming to an end. IT organizations now require an industrial approach to managing IT as a factory. The biggest challenge achieving that goal is no longer the technology but rather the culture of the IT organization.
