Posts by krishnan:
- It helps them emerge much stronger in Kubernetes community. Already, Red Hat is the second largest contributor to Kubernetes after Google. With Microsoft aggressively recruiting Kubernetes contributors and gaining leadership role in the committees and AWS entering CNCF and ramping up their open source efforts, keeping the leadership role in the open source community becomes a competitive advantage. By acquiring CoreOS, Red Hat is strengthening their leadership in the community and it will help them in selling to enterprise IT
- Red Hat has a strong play in every layer of the modern enterprise stack, from operating system to container engine to orchestration to the developer platform layer. Bringing CoreOS inside Red Hat strengthens this advantage
- CoreOS was not a threat to Red Hat, but it is definitely a pain in both container space and public clouds. Taking out a potential threat is a smart way to establish long term relevancy even if it comes at a huge (as per Red hat’s M&A standards) cost
- Canonical’s Ubuntu has a lead in the public clouds. By buying CoreOS, which has both developer and startup mind share, Red Hat can fend off Canonical as well as public cloud providers own version of Linux
- It will be interesting to see how Red Hat fits CoreOS with Project Atomic and Red Hat OpenShift. CoreOS has competing offerings in both container operating systems and application platforms. It is critical for Red Hat to position these offerings in a way that doesn’t confuse the market
- They will have to retain the Kubernetes contributors for a few years to get better ROI from this acquisition. It will be interesting to see how they fend off the talent poaching after the vesting period
- Competitors are going to get aggressive in getting the attention of enterprise customers. Public cloud providers like AWS and Azure are going one step above Kubernetes to make Container as a Service seamless with AWS Fargate (which will integrate with AWS EKS soon) and Azure Container Instances. They will try to go up the stack to lock down customers inside their service
- Other platform providers like Pivotal, Docker and Mesosphere will recalibrate their strategy after this acquisition. As we pointed out in this analysis, we expect Pivotal to get rid of the technical depth underneath the platform and focus on a more developer centric platform higher up in the stack with their Spring investments and future Functions as a Service offering. We will wait and see how Docker and Mesosphere react to this development
- Expect to see some other startups in the Kubernetes space to be acquired by other enterprise vendors. Oracle is ramping up their cloud efforts. Both IBM and SAP are focussing more and more on Kubernetes. These large vendors will definitely need help in making their offerings attractive to modern enterprise and this will lead to some more acquisitions in the next year or so
- One of the early adopters of both Docker containers and Kubernetes, OpenShift is built entirely on industry standard components for any container platform
- With the focus on Developers and DevOps workflow, OpenShift abstracts away some of the complexities associated with Kubernetes deployment
- With Red Hat’s other products in their portfolio, OpenShift can emerge as the RHEL equivalent for Application Infrastructure
- Pivotal’s move up the stack with SpringOne platform and announcements about future “serverless” offerings is a smart move and is in tune with their developer focus. The developers are kingmakers and Pivotal is well positioned to empower them with their focus on Spring and “serverless”
- With their data assets and a strong consulting business, they are well positioned to help enterprises in their modernization journey
- Mesosphere has integrated well with Kubernetes and they are well positioned to support both traditional web apps and data intensive workloads. Their strength in supporting big data frameworks makes them a strong player in the application development platform space
- Apache Mesos is proven to be a mature enterprise platform and DC/OS on top of Mesos for cluster management makes them a credible enterprise platform
- AWS leads all the cloud providers in the sheer number of services they offer to customers. Their push towards serverless which started two years back is now moving to other areas such as containers (AWS Fargate), Data Services (AWS Aurora Serverless), etc.. At Rishidot Research, we deeply believe in higher order abstractions playing a critical role in enterprise IT (we were only of the early believers in PaaS and ran a conference dedicated to it) and we strongly advocate the “serverless” abstractions as the path forward. AWS serverless abstractions other than Lambda is still in early stages and we would expect the services to become even more seamless and autonomic (eg: Without having to describe the limits on resources. AWS should handle that seamlessly with better ways to limit runaway costs)
- Even though they are slow to push container services and Machine Learning, they are pushing hard in these two areas. AWS Fargate is how container services should be and might provide a competition to many Cars and PaaS vendors in the market. I would characterize their approach to “giving choice to customers” as an underdog marketing approach in areas where they are not a leader in the market. Both containers and ML are areas where mindshare is still not there with AWS. By touting “user choice”, AWS is trying to catch up with other cloud providers
- One of the criticism I heard from users during AWS Re:Invent 2017 conference is on the interoperability of their services. I would expect AWS to focus on fixing the issues and solving the pain points faced by users of multiple AWS services. I would also like to see Amazon cut down the complexity in the consumption of services. The sheer number of services offered by Amazon makes it a daunting task for decision makers as they plot their strategy. Anything Amazon can do to tame this complexity beast will be helpful. A good example is AWS Fargate service. At Rishidot Research, we believe in the composability of the different layers in the IT stack but it shouldn’t come at the cost of increased complexity to consume the services
- Both in terms of their service offerings and the customer momentum, AWS has the lead in the market. One trend I observed during the recent Re:Invent is that the size of the IT team makes a difference in organizations going all in with AWS. Large businesses with smaller IT teams are more open to going all in with AWS. If you are an enterprise decision maker wanting to go all in with a single cloud provider, the size of your IT team will impact the decision making process.
- Microsoft Azure is steadily increasing their public cloud marketplace. The main Azure development is driven mostly by the existing relationship between Microsoft and the IT decision makers but they are changing minds among OSS developers and the younger generation of developers by a strong OSS push. Being the largest contributor in terms of the number of lines of code (because of .NET being open sourced), Microsoft has gained the critical credibility needed to make Azure palatable to OSS developers. By releasing services like CosmosDB, Microsoft has been working hard to gain developer adoption to Azure cloud services
- Microsoft may not be a leader in Containers but they are investing heavily in hiring Kubernetes talent. Many pundits (including myself) have linked AWS’s embrace of Kubernetes and CNCF as an indication of standardization around Kubernetes but Microsoft’s investment is critical because they are now in a position to neutralize Google from pushing Kubernetes in a direction suitable for them
- I would like to see Microsoft focus more on making their services more “serverless”. They have necessary components including service fabric and others to move in that direction. I am expecting some announcements in this direction from Microsoft in the next Build conference
- Microsoft is still an underdog when it comes to ML and AI workloads. They do have a solid technology to make Azure an attractive destination for such workloads. I am yet to see a coherent go to market strategy in this case
- With Azure Stack (AS), Microsoft gave a great story for hybrid cloud/edge computing in last year’s Build conference. The use case with Carnival Cruise Line is a perfect example of Azure Stack. The way they are integrating serverless technologies with Azure Stack will make AS an attractive option for edge computing use cases
- After a slow start, Google Cloud got attention through two open source projects, Kubernetes and Tensorflow. With Kubernetes, Google is uniquely positioned to help enterprises “run like Google”. Even though they showcased some customers in last year’s Google Cloud user conference, they are yet to publicly demonstrate continued success with enterprises. I am hoping to see more customers in this year’s conference
- Even though Google got early momentum with Kubernetes, AWS and Azure have since caught up with Google in terms of both mindshare (in the case of Azure) and market share (in the case of AWS). I would love to see Google showcasing technology that will make their cloud more attractive than both AWS and Microsoft when it comes to container workloads
- Google cloud is a clear leader in ML and AI workloads on the cloud. They took a more opinionated approach with Tensorflow and it is paying off, mainly due to the success of Tensorflow as an OSS project. They need to demonstrate that they can capitalize on this early success this year
- Google has an advantage in Big Data services but AWS and Azure are catching up fast
- IBM started its cloud push much earlier than Oracle and even before Google or Microsoft showed their seriousness towards enterprise adoption of cloud. In spite of their acquisitions around cloud data centers, data services and even DevOps, they are still lagging behind the top three cloud providers in both mindshare and market share (at least, with AWS and Microsoft). More than anything else, there is absolutely no clarity on IBM’s cloud journey. After betting on OpenStack and CloudFoundry early on and, now, Kubernetes, they are yet to demonstrate a clear path towards success in the cloud. In 2018, I expect to see a more coherent cloud story from them
- IBM Watson was supposed to help IBM gain on cloud computing. Even though there are some customer stories based on Watson and IBM Cloud, we need to hear more in 2018
- Oracle was the last to enter infrastructure as a Service business among the top cloud vendors. They are still in early stages even though they have made some announcements related to containers and container orchestration. I expect to see them take a deeper plunge in the Kubernetes ecosystem even though they are yet to demonstrate that they can work well with other vendors in an open source project.
- They need to shore up higher order services if they have to compete effectively with AWS and Azure. They cannot just rely on their database service as the path to cloud success and they need to compete with AWS on the breadth and depth of higher order services. Looking forward to hearing from them on this topic in 2018
- Integration with multiple data sources
- Powerful filtering capabilities in the UI to blend data across various sources and functions to gain insights
- powerful machine learning capabilities
- RackN team has vast experience in the infrastructure provisioning and they have put their expertise in building this powerful platform.
- Decoupled approach to automation makes the platform lightweight and simple. Keeping orchestration separate helps users use any tool of their choice whether it is Ansible, Terraform, Puppet or Chef
- The success of Kubernetes and the hooks offered in the recent versions helps RackN platform provide the bare metal infrastructure for the containers and Kubernetes clusters can be deployed without the additional overhead of orchestration tools
- They have distinct advantage over the competitors with the powerful workflow automation feature
- They have to overcome the resistance to change. Most data center people are used to tools like cobbler and foreman. They need to convince them of RackN’s value. Essentially, they will be fighting against the human inertia
- In this era of cloud, they need to make a convincing case that Baremetal as a Service offers competitive ROI
- Containers are getting big and their integration with Kubernetes is going to give them an opportunity to emerge as the infrastructure for containers
- We have seen evidence that companies move back to their own data centers from the public cloud when they reach a certain scale (think Dropbox). RackN, with their competitive ROI, can emerge as a strong player in this trend
- Infrastructure companies can easily find a partner (or a potential acquisition target) in RackN
- Companies like Red Hat and Canonical with their server provisioning platforms will compete hard against RackN. But RackN has an advantage in terms of heterogeneity in the operating systems they support
- Public cloud market could grow big putting pressure on companies in the datacenter space
- Oracle’s cloud strategy involves basic IaaS which competes with AWS on the “enterprise-centric” pricing strategy and vendor claims about better performance and “PaaS” (quotes used to differentiate Oracle’s definition of PaaS from the traditional industry definition of PaaS) which includes their middleware offerings and database service. At this point in time, their differentiating factor from the industry leader AWS is pricing
- Set of container-based services on top of their IaaS to compete with container offerings by every other cloud provider. This includes Kubernetes based container service, Oracle container registry and Oracle container pipelines
- Announcement of an open source functions as a service platform. It is an early stage software than a service on top of Oracle IaaS. However, with their middleware tools and IaaS, this could be a Oracle cloud service in the future
- Announcements regarding AI strategy and blockchain tools in their cloud
- Oracle 18c, their enterprise database offering with automation based in machine learning and enterprise grade SLAs
- Powerful NLP engine to handle machine data, add context and give customization options to users
- Starting with Splunk data (with an investment from Splunk, of course) gives them an easy on ramp to enterprise IT
- Their initial focus on Security will help them get the attention of IT decision makers
- Autopilot feature that provides a more pro-active approach to security might serve as model for future autonomic computing platforms
- They are a startup pushing a newer technology in the enterprise market. The barrier to entry for startups in enterprise is high. However, their partnership with Splunk should help them
- They provide on-premise deployments which makes it difficult for the learning engine to continuously improve. But they are tapping into the anonymized meta data to help the learning engines learn from user behaviors. This will work well with modern enterprises but they may have trouble convincing enterprises in highly regulated verticals. It is not a weakness for Insight Engines alone but for any company trying to build AI systems that can be deployed on-premises. To overcome this, Insight Engines, as a pioneer in this space, has to convince the customers to share their metadata with them. It is a potential weakness but also an opportunity for them to emerge as thought leaders
- Insight Engines has the first mover advantage and they are attacking low hanging fruits (machine data and security) with a more powerful NLP engine. They can easily broaden their product portfolio going forward
- As we embrace modern stacks with deeper and deeper levels of automation, ML and AI are going to be the next wave of innovation. The early innovations in this kind of autonomic IT will come around user interface and user experience. Insight Engines is well positioned to take advantage of the trend
- Many established players collect lot of machine data (including Splunk) and it is a logical next step for them to attack the low hanging fruits like NLP for UI/UX. Though it is a threat, it is also an opportunity
- Open source NLP engines can come and disrupt the market. OSS need not come from the traditional IT companies but also from end customers who develop ML and AI engines for their internal use. There is also an opportunity for Insight Engines to lead here but OSS by startups is not easy.
Today, Red Hat, the open source company focussed on enterprise IT, announced the acquisition of CoreOS, its competitor in the container market (Red Hat press release). This is clearly shaking up the enterprise application platform market and, definitely, the Kubernetes community. CNBC puts the cost of the acquisition at $250 Million, making this one of the largest Red Hat acquisitions. In this quick analysis, we take a look at this news and how it impacts the modern enterprise.
As a startup, CoreOS went directly at Red Hat, trying to position themselves as the operating system for containers. They also built a platform called CoreOS Tectonic as the multi cloud Kubernetes distribution going against Red Hat’s OpenShift Container Platform and other application platforms in the market. CoreOS is also one of the biggest contributor to the Kubernetes project and there was speculation that they will get acquired by one of the enterprise cloud providers to effectively compete with Red hat in the space.
What it means for Red Hat?
This helps Red Hat in many ways
I have reached out to Red Hat Analyst Team with some questions and I will update this post after we hear from them.
What it means for the competition?
This definitely starts the process of consolidation in the Kubernetes community
What it means to Customers?
Anytime there is a consolidation in any market, customer lose choice but this round of consolidation is happening in an open source community which has emerged as a standard for container orchestration. In a way, such a consolidation in this space might accelerate container adoption and a stronger movement towards IT modernization. Many enterprise IT organizations have a strong relationship with Red Hat and this acquisition will help them stick with Red Hat as they move towards containerized workloads.
Overall an interesting acquisition by Red Hat and it all depends on how well they position the combined offerings and how well they integrate with existing products. Let us see how it shapes up.
Based on our agenda to focus on Cloud Native Landscape in the first half of 2018, this post will take stock of the major application platforms to set the context for further discussions in the coming weeks and months (see our post on public cloud for the same reason). In this post, we are discussing the major platforms based on the signals we get from the data we collect from enterprise users. We are also following other platforms closely and our future research will include them.
Red Hat OpenShift
In 2018, we expect to hear from Red Hat on their “serverless” strategy. With the success of AWS Lambda and other serverless offerings in the market, the enterprises want to have clarity on Red Hat’s strategy on this. With their JBoss portfolio and their investments in Apache OpenWhisk, we expect to see some announcement to fill this gap.
We expect Pivotal to move out of CloudFoundry underneath their platform and re-platform completely on Kubernetes and Docker based containers (currently Moby Project). If their core focus is on developers, they should use industry standard commoditized components underneath and focus only on developer experience. We are Day 1 advocate of the CloudFoundry project and we had invited CloudFoundry customers to keynote in our Deploycon conferences but the success of Kubernetes since 2014 makes it critical for Pivotal to focus on building the best developer experience entirely on top of Kubernetes and eliminate any technical debt underneath. With their strength on Spring platform, they can emerge as a strong Kubernetes vendor helping enterprise modernization
Even though they have integrations with many modern developer and DevOps tools, we expect Mesosphere to focus on building a seamless developer experience this year. With the operational maturity underneath (Apache Mesos) and Kubernetes for container orchestration, having a solid developer experience will help Mesosphere DC/OS
There are many Kubernetes based container platforms we didn’t consider for this post as they don’t fit into the App Dev Platform definition. We are closely watching Docker Enterprise, Apprenda, SAP Cloud Platform and it will be part of our analysis in the future.
A very happy new year from Rishidot Research. As we enter 2018, the pressure on CIOs to modernize their IT is going to increase significantly. Any further delay will hurt the business bottom line. At Rishidot Research, we have our hands full on a research agenda focussed on Cloud Native Computing landscape and CIOs will find our research very valuable for their modernization strategy. As a first step, and also to set the context for our discussions in the coming months, we will take stock of the major public cloud vendors and where they stand against their competition.
Amazon Web Services (AWS) is the leading cloud vendor by a huge margin. The scale and the momentum in the recent AWS Re:Invent 2017 is a clear indication of this trend. Now AWS’ user conference is comparable to the traditional IT vendors and the number of CIOs and other decision makers I came across in this event indicates that enterprises are eager to embrace public clouds. It is only natural to start our analysis with AWS.
Amazon Web Services
We are also closely tracking both Alibaba cloud and Huawei cloud. We do notice that Alibaba cloud is fast adding new features but we are waiting to hear from them on their US traction. We will include these two cloud providers in our future analysis.
Disclosure: AWS, Microsoft and Google paid for travel and stay to attend their user conferences in 2017
Accelerite, the Silicon Valley based company focussed on Hybrid Clouds and Big Data, today announced the next version of their data analytics product, ShareInsights 2.0. ShareInsights is their self service data analysis product focussed on taking the grunt work out of business users and make it easy for them to gain critical insights needed for their organization. Their product offers data preparation (ETL), OLAP, visualization and collaboration in one single interface, making it an end to end stack for data analysis.
Ever since big data infrastructure became mature, mainly driven by open source technologies, the focus has shifted to data analytics and machine learning. From offering superior customer experience to gaining critical business insights from disparate sources to developing product roadmaps, data analytics is becoming the core competency of any modern enterprise. The biggest pain points felt by modern enterprise decision makers were in data analysis, data transformation and data collection. The big expectation from the decision makers is to have a tool that seamlessly breaks down the data silos across disparate set of data sources. One of the biggest asks from business to enterprise decision makers is a self service analytics tools which takes the groundwork out of getting the data ready for analysis.
Company and Product
Shareinsights is Accelerite’s big data analytics tools that is focussed on offering business users a self service tool to gain insights from large volumes of data. Accelerite also has Rovius hybrid cloud platform and Concert for IoT. Unlike Rovius which is an acquisition, Shareinsights was built from ground up with a single goal of simplifying data analysis and take any pain out of business users that can slow them down. The key focus in their product is speed whether it is the speed of getting started with an analytics product using their platform or the platform speed itself. The platform can run on Hadoop or Kafka, easily integrating with your existing tools in your organization. The platform accelerates the lifecycle from infrastructure operator to business user, by streamlining the flow from data preparation to transformation to visualization.
With Shareinsights 2.0, it is easy to process large volumes of data from multiple sources, whether it is a CSV file or API from a third party service. It is easy to blend data from across multiple functions inside the organization and gain insights beyond what is usually available in legacy analytics tools. They have also included vast library for machine learning algorithms, making it easy for even business users to run machine learning models on top of data and gain critical insights.
The typical customer expectation from a tool like Shareinsights are:
Shareinsights 2.0 appears (from the demo we used for our evaluation) to solve these needs and we expect the tool to meet the needs of modern enterprises. We will continue to watch their progress and talk to customers in the future to gain better insights on their product in the future.
Yesterday at Dockercon EU, Docker announced its support for Kubernetes on the Docker Enterprise Edition, Docker Community Edition as well as its desktop apps as well as the Moby project. This is a significant shift for a company that almost broke the open source community around the then Docker project. They wanted to push the hooks for their orchestration and management plane into the containers under the “batteries included but swappable” marketing campaign. Since then, the wind has blown in the direction of Kubernetes at the orchestration level and the conversation has effectively moved from the standardization around containers to standardization on orchestration plane. In this post, we will discuss the implication of this announcement in the market and how it impacts IT decision makers.
Docker’s foray into Kubernetes World
Yesterday Docker pre-announced the availability of Kubernetes on Docker platforms and the Moby project citing the shared roots between Docker community and Kubernetes community. They also announced that they would make vanilla Kubernetes available and stay close to the recent version instead of the Red Hat model of releasing stable releases for OpenShift Container Platform. According to Docker, there will be better collaboration between the Moby project and Kubernetes project. The end users get the option of selecting Kubernetes or Swarm for orchestration.
The State Of Developer Platforms
It is all about application platforms. How do you empower developers in your organization to seamlessly deploy apps ensuring faster time to market? How organizations enable them depends on the abstraction which, in turn, depends on the nature and requirements of the application being deployed. The early days of cloud saw the debates of IaaS+ vs PaaS and we see similar trends in the era of container native workloads. Kubernetes is fast gaining mindshare, driven by the declarative approach it offers in the automation of container native infrastructure. The quest to pick the right abstraction needed for various applications still see the same kind of demarcation we saw in the early days of cloud computing. It is IaaS+ (driven mainly by Kubernetes even though Mesosphere DCOS and Docker Swarm are other competing platforms) vs the platform abstraction at the developer layer enabled by platforms like OpenShift and Pivotal CloudFoundry (picking Pivotal CloudFoundry specifically because I don’t see any other credible vendor in that ecosystem) vs the serverless or Functions as a Service offerings. The usage patterns range from monolithic and web apps in IaaS+ to Modern apps including Microservices on developers focussed platforms like OpenShift and CloudFoundry to event-driven Microservices in the Serverless/FaaS platforms.
The announcement by CloudFoundry that Kubernetes will become the Container Runtime for CloudFoundry platform combined with Docker’s announcement that Kubernetes will be one of the choices in orchestration plane puts Kubernetes as the core component in the container native application platforms. Kubernetes, by itself, has limited impact but it is emerging as the core component of modern day platforms whether it is IaaS+ or modern PaaS or FaaS. Both Pivotal CloudFoundry and Docker are positioning their support for Kubernetes as giving a choice to their customers. While this may be true in the short term, there is a high chance that Kubernetes will emerge as a standard in the container orchestration and be a standard component of any developer-centric platform.
In that sense, Kubernetes is fast emerging as a standard for container orchestration. But, we want to discount any notion that Kubernetes has won the platform wars. The platform market is wide open with many of the workloads still in VM machines and Kubernetes adoption in production is still in early stages. Functions as a Service (as a public cloud service) or a FaaS Platform that is multi-cloud and agnostic of orchestration layer may take the steam out of Kubernetes just like how Kubernetes took the winds off Docker momentum.
Considerations for IT Decision Makers
This makes the decision much easier for IT decision makers and it helps them consolidate their platform choices without worrying about whether the platform supports Kubernetes or not. If your organization has already invested in Docker Platform, this makes it easy to have a mixed environment where Kubernetes can be used for managing dev and test clusters and Docker Swarm for production. The next version of Docker Enterprise Edition and Docker Community Edition will make this easier for your organization. If you are not a Docker shop and want to have a choice in the container orchestration, it makes sense to go with Docker Platform. Otherwise, there are other choices from established vendors like Red Hat OpenShift or Pivotal’s CloudFoundry Platform. Between Red Hat OpenShift and Pivotal CloudFoundry, the decision is mostly cultural. If you are an IT-centric organization, Red Hat OpenShift Container Platform is well suited for your needs. If you are a developer focussed organization, Red Hat’s OpenShift Online or OpenShift Dedicated or Pivotal’s CloudFoundry are better options. Depending on the tolerance level of the organization for betting on startups, there are other options like Mesosphere DCOS, Rancher Labs, Heptio and many others. But if your end goal is to embrace Functions as a Service, you could still use containers to encapsulate the backend services but we would strongly recommend that you bet on multi-cloud, container orchestration agnostic platforms. It doesn’t make sense to embrace Kubernetes just for using FaaS.
Docker’s move into Kubernetes is the next logical step for them after they failed to capitalize on the momentum behind their container mindshare. This also makes them a much easier acquisition target as every big company has bet their modern stack strategy on Kubernetes. It will be interesting to see where Docker goes from here as Steve Singh takes full control with the newer round of funding expected to happen soon.
RackN, the startup based in Austin, had launched their platform in beta last week. RackN aims to simplify infrastructure provisioning through a layered approach which decouples provision, control, and orchestration, giving users more flexibility without losing simplicity. In this research note, we will analyze their platform.
Data center infrastructure provisioning is an old trade helping enterprises provision data centers to meet their IT needs. However, with the advent of cloud, large enterprises and data center providers want to provision their data centers just like how Amazon and Google are provisioning their own data centers. The flexibility and speed enjoyed by the web-scale cloud providers give them a unique advantage in ROI which traditional data centers cannot match. However, for the past few years, there are tools (some are new, and others are an evolution of the traditional provisioning tools) that are enabling seamless provision of data center infrastructure leading to a new category called Bare Metal as a Service. This is partly due to the evolution of data center priorities to match the web-scale cloud providers and also due to the success of containers in the enterprise. Baremetal is a more natural fit for containers than virtualized environments (which are more of a stop-gap arrangement to fill a gap) and the success of Kubernetes has brought new found interest in Baremetal as a Service.
RackN platform is focussed on infrastructure automation but takes a more layered approach to automation. It decouples provisioning, management, and orchestration into different layers, thereby simplifying the processes while also giving customers flexibility on the orchestration tools they want to use. This composable approach to automation coupled with a powerful workflow feature based on their library, helps anyone get started with provisioning in 5 minutes and realizing tremendous ROI in the process. RackN platform brings a level of automation to underlying infrastructure that makes data center provisioning more competitive in this cloud world.
Cobbler, Foreman, Canonical MaaS, Matchbox
RackN is in an interesting situation with tremendous hype in containers and the performance advantage of Baremetal as a Service in the container dominated world. Their advantage with simplicity puts them in an advantageous position compared to all their competitors. But they need to gain mindshare (and eventually market share) to compete effectively
Disclosure: RackN was Rishidot Research client in the past
Oracle., the enterprise giant of the legacy era, hosted their annual user conference Oracle OpenWorld last week shed some more light on their cloud strategy. Oracle made some announcements focussed on cloud computing, Artificial Intelligence, and Blockchain but it came out more like an organization trying to jumpstart their vehicle to catch up with competition than a thought leader pushing innovation. Oracle is almost a decade late into the cloud game and their efforts to compete is still focused on marketing than showcasing any substance. In this analysis, let us dive into Oracle’s strategy for the modern enterprise stack
After dismissing cloud for the better part of the decade and then calling their legacy enterprise applications as cloud, Oracle started focussing on Infrastructure as a Service to take on AWS, Microsoft Azure, Google Cloud and IBM Bluemix. They built an infrastructure service from the ground up, tapping into AWS and Azure engineers, focussing on Compute, Storage, and Network. Then they expanded their offerings to include containers. Here is Rishidot Research’s SWOT analysis on Oracle IaaS strategy earlier this year.
Oracle OpenWorld 2017 Announcements
Oracle made many announcements at this year’s OpenWorld and we are highlighting some of the important ones on their cloud offerings
Oracle is building a infrastructure as a service offering with compute, storage and network. They are also adding container services to the mix. Compared to the top three cloud providers, AWS, Microsoft Azure and Google Cloud, Oracle Cloud is still at a barebones stage when it comes to the depth of their offering. We expected a bunch of higher order services on top of their IaaS but we didn’t see any announcements for newer services or even a coherent roadmap to match the depth of services in the other three providers. Oracle spent the news cycles around OpenWorld focussing on a strategy that is more about reducing their bleeding than convincing newer customers about Oracle Cloud as the infrastructure for innovation. They spent way too much time in the Larry Ellison keynote on their pricing strategy compared to AWS than showcasing innovation that could make their competitors sweat. Even their pricing strategy was more about convincing the customers of Oracle database and applications to use their IaaS than enticing newer customers to start embracing their cloud. We think that the pricing strategy is more old-fashioned and focussed on enabling their salespeople to close big deals than a pricing strategy for the modern era.
It is important for the market to have Oracle as a strong player but, to compete effectively, Oracle has to go at full speed to build depth in the services they offer on top of IaaS. Building iteratively is not going to either help them close the gap with the top three providers or in giving confidence to decision makers that betting on Oracle IaaS is a smart choice. Between now and the next Oracle OpenWorld, I would love to see Oracle add a wide range of higher order services so that enterprise customers can really innovate on top of Oracle cloud. Modern enterprise CIOs are more focussed on innovation than cost savings or iterative performance improvements. They need a powerful infrastructure on top of which their developers can innovate. It is critical for Oracle leadership to understand this need and build a compelling offering to outcompete AWS, Azure and Google Cloud.
Oracle’s container strategy is on the right path but the lack of higher order services is going to hinder the developer adoption of their container service. They do offer a suite of tools to manage the containerized applications from development to production but it is still barebones and they have their work cut out in making this offering more compelling as Amazon ECS or Google Container Engine.
I am glad to see Oracle talking about AI and Blockchains as a part of their modern stack and I am hoping that they have a production ready set of tools available by next OpenWorld.
Recommendations For Enterprise Decision Makers
If you are an Oracle Customer wanting to migrate your applications to the cloud, it makes complete sense to consider Oracle IaaS for your migration needs. However, this is recommended for the migration of existing applications than building any net new applications. They have limited set of services for building next gen applications. Wait for their offerings to mature before using Oracle cloud for newer applications.
If Oracle tech stack is not critical for your applications, AWS, Microsoft Azure or Google Cloud have a wide range of services needed for the modern applications. We strongly recommend these providers for your next gen applications at this point. Oracle can still evolve fast to compete with these providers by increasing the breadth and depth of their higher order services but they are not there yet.
In spite of their late start, Oracle has shown seriousness and commitment towards a more coherent cloud strategy. They still have a long way to go before they can catch up with their competitors. Right now, their IaaS is quite attractive for migrating existing applications built on Oracle stack because of the aggressive pricing but their cloud is not recommended for net new applications. This may change between now and next OracleWorld if they accelerate rapidly, either by building or acquiring companies, to offer higher order services. We will have to wait and see. Rishidot Research recommends enterprise decision makers to closely watch their roadmap for the next year before betting their strategy on Oracle Cloud.
Insight Engines, the San Francisco based startup focused on making machine data actionable, announced the general availability of Cyber Security Investigator and, also, showcased how Amazon Alexa can be tapped to query from Cyber Security Investigator. In this note, we will do an analysis on this announcement.
AI in enterprise is relatively new. Even though enterprises are slowly embracing machine learning and other AI models to dig deeper into their customer data and make business decisions, there is very little progress in using AI to take advantage of machine data. There are plenty of analytics solutions that helps Operations teams optimize their decision making process. But the market is still in infancy when it comes to using ML to automagically do operations or use AI technologies like NLP to develop a better user experience for the machine data. Imagine how DevOps can be done more optimally if developers or even other stakeholders like business users can take advantage of NLP to interact directly with machine data. These are just beginning and we can’t imagine what AI can do to autonomic computing with our current understanding of the landscape.
Insight Engines is an interesting startup in the up and coming field of AI in enterprise IT. It is too early in the market but offers potential opportunities for enterprises to do IT more optimally and optimize the use of human power in house by involving more stakeholders and by reducing the learning curve.