About the Author
Michael Azoff
With over 17 years analyst experience, most recently at Ovum/ Informa, Michael Azoff joined Kisaco Research, the company behind the AI Hardware and Edge AI Summit series, in 2020 as Chief Analyst.
Eitan Michael Azoff, PhD, MSc, BEng.
HQ’d in Kisaco Research’s London office, Michael's current focus is launching Kisaco Research vendor product comparison reports with the new Kisaco Leadership Chart (KLC) analyst chart. The first KLC is also the first analyst chart in the AI chip industry, with 16 vendors having participated in the research.
In his career Michael worked at Rutherford Appleton Laboratory building simulators for electron and hole transport in semiconductors for UK national and European community research projects and published papers in learned journals. He then turned to building neural networks and created a startup selling his Prognostica Microsoft Excel add-in for time series forecasting, and wrote a book on the topic for publisher John Wiley & Sons in 1994.
Since 2003 Michael has worked as an IT industry analyst covering software engineering topics, from agile and DevOps, to application lifecycle management and cloud native computing. He started covering machine learning when deep learning emerged as the most recent wave of interest in AI and left his position as Distinguished Analyst at Ovum/Informa to join Kisaco Research and help build an analyst capability within the company.
My analyst coverage areas at KR Analysis
My first research project at KR was to create the first analyst comparison chart for AI chips. We invited AI chip producers to participate and were fortunate to have 16 vendors participate from across the globe: USA, UK, France, and China, and a mix of established players (Nvidia, Imagination, Intel, and Xilinx, to startups.
Our analysis showed that the market naturally fell into three areas of hot activity:
▪ Data centers and high-performance computing environments (HPC): here large boxes are installed and the aim is to achieve maximum performance for training and inferencing AI systems. The buyers are cloud hyperscalars, national research labs and agencies, and some large enterprises with big investments in AI.
▪ Small edge: the opposite end of the spectrum, building the smallest useful chip possible to sell as cheap as possible and embed in edge devices. AI is inferencing here.
▪ Automotive: an active industry in AI but highly regulated creating hurdles and technology adoption cadences that can be challenging for suppliers. AI is mainly inferencing here (for systems installed in vehicles).
We produced four Kisaco Leadership Charts out of this research.
We are also researching the machine learning (ML) software tools space, and our first report here is ML Lifecycle Solutions. The biggest challenge for enterprises is taking the research AI systems developed by their data scientist and deploying these into production at scale. Using a host of open source tools to achieve this is possible but time consuming to build and maintain, as well as prone to breakdown. This is why the ML lifecycle solution space exists.
Finally, in our first batch of KR Analysis reports we produced the KLC on engineering application lifecycle management (ALM) solutions. While ALM has been in existence as a distinct practice since KR Analysis and Michael Azoff introduction © Kisaco Research. All rights reserved. Unauthorized reproduction prohibited. 4 around 2003, it continues to evolve. We found the engineering and highly regulated industries relying on engineering and compliance oriented ALM to help manage risk and complexity.
-
Motivation
Modern software development has been revolutionized by first agile methodologies and then what can be called the continuation of agile from development into operations: DevOps. Where continuous integration (CI) and continuous testing are central to agile, bringing in automation to reduce human error, improve efficiency, and speed up many chores in the development process, the same can be said of continuous delivery (CD) being a central part of DevOps. Tool automation is important in supporting the radical changes that agile and DevOps bring to software development. With the growth of software development thanks to the internet and digital transformation and the proliferation of development tools in the eco-system, there is greater need for tools that can act as platforms, hence this Kisaco Leadership Chart (KLC) focuses on DevOps platforms, integrating with the tool ecosystem.
However, DevOps is more than just about tools, and the impact of DevOps on organization culture continues to be just as challenging as agile, perhaps more so, requiring even more silo groups within the IT and organization landscape to co-work. Those organizations that succeed reap significant rewards: the State of DevOps series of open reports cite the success in the stock market of companies practicing DevOps at the highest maturity levels.
-
What you will learn
- You will learn the makeup of the DevOps tools market and the role DevOps platforms play.
- The latest trends in DevOps technology are detailed, and the current market outlook and drivers for DevOps adoption are examined.
- For readers new to DevOps we delve into what it is and how to assess your organization’s maturity along the path to maturity. Our DevOps assessment levers chart internal adoption of DevOps and also how to work DevOps style with external suppliers and partners.
- Our KLC selects four innovative DevOps platforms and examines them head-tohead. The KLC ranks these vendors according to strength of features and strength of market execution.
- We provide in-depth profiles on each participating vendor with strengths and weaknesses assessed.
-
Contents
Kisaco Research View 2
Motivation 2
Key findings 2
DevOps market and technology landscape 3
Technology trends 3
Market trends 4
DevOps 101: an introduction for newbies 5
DevOps origins 5
DevOps maturity 5
DevOps assessment 6
Solution analysis: vendor comparisons 8
Kisaco Leadership Chart on DevOps platforms 2021 8
DevOps platform vendor comparisons 8
The KLC chart for DevOps platforms 9
Vendor analysis 11
Flexagon, Kisaco evaluation: Contender 11
Kisaco Assessment 13
IBM, Kisaco evaluation: Leader 14
Kisaco Assessment 16
Opsera, Kisaco evaluation: Emerging Player 17
Kisaco Assessment 19
Progress, Kisaco evaluation: Leader 20
Kisaco Assessment 22
Appendix 23
Vendor solution selection 23
Inclusion criteria 23
Exclusion criteria 23
Methodology 24
Definition of the KLC 24
Kisaco Research ratings 24
Acknowledgements 24
Author 24
Copyright notice and disclaimer 25
-
Figures
Figure 1: Enterprise DevOps platform technology stack
Figure 2: A three stage DevOps maturity model
Figure 3: Assessing the state of DevOps adoption within your organization
Figure 4: DevOps assessment for working with external suppliers
Figure 5: Heat map analysis of participating vendor solution technical features
Figure 6: Kisaco Leadership Chart on DevOps platforms 2021
Figure 7: Kisaco Leadership Chart on DevOps platforms 2021: ranking of vendors
Figure 8: FlexDeploy DevOps platform key features
Figure 9: The IBM UrbanCode suite
Figure 10: Opsera’s continuous orchestration works across the broad DevOps eco-system
Figure 11: The Chef product portfolio
Figure 12: Chef Compliance
-
FAQs
1. What is the KLC?
The Kisaco Leadership Chart (KLC) is KR Analysis’s take on the classis industry analyst chart in which vendor products are assessed and their scores plotted on a chart comprising four quadrants: Leader, Contender, Innovator, and Emerging Player. The x-axis represents strength of technical features, the y-axis the strength of market execution and strategy, and the size of plotted circle represents market revenue normalized to the strongest participating player in the research.
In researching the KLC we receive privileged information from a vendor. As explained in question 3, participating vendors are actively engaged in our research. Confidential privileged vendor information is not disclosed in our report but helps us assess vendors in our analysis.
2. What is the vendor selection process for a KLC project?
KR Analysis creates a shortlist of vendors to invite to the research project. The aim is to include the leading players as well as innovative smaller players, across startup and established vendors. KLC research can at best be representative of the market and is not designed to be exhaustive – in some markets the sheer number of players would make an exhaustive KLC unmanageable, in smaller markets we are still dependent on vendors agreeing to participate.
We do create KR Analysis Technology and Market Landscape reports in which we typically list the players in the markets with thumbnail profiles providing information such as company leadership, location, funding status, and main product(s) details. While we cannot guarantee exhaustiveness, the landscape report does aim to list the most important vendors and does not require vendor participation.
3. In a KLC what does participating entail for a vendor?
First of all, we do not charge vendors to participate in a KLC. Participating vendors need to be actively engaged in a KLC research project, this involves completing a comprehensive questionnaire, which we score and use as the basis for positioning the vendor in the report’s KLC. We also hold a deep dive briefing and engage in plenty of Q&A. Finally, we research publicly available material on the vendor and its product(s) to complete our final view of the vendor.
4. Why are some notable vendors missing from the report?
As explained in question 2, we do invite the leaders in a market segment we are researching, however not all such players agree to participate. As explained in question 3, participating involves active engagement and example reasons vendors offer for declining our invitation are, often ending with “...but please consider us next cycle of the report.”:
- We are in the midst of an event in which our relevant staff do not have the time to engage in your process.
- We are going through a major change in strategy or product re-architecture and the timing is not right for us to participate.
- We are about to have our IPO and this is not the right time to participate.
- We are about to launch our flagship product and the report timing is not right for us.
-
About the Author
Michael Azoff
Chief AnalystKisaco ResearchWith over 17 years analyst experience, most recently at Ovum/ Informa, Michael Azoff joined Kisaco Research, the company behind the AI Hardware and Edge AI Summit series, in 2020 as Chief Analyst.
Eitan Michael Azoff, PhD, MSc, BEng.
HQ’d in Kisaco Research’s London office, Michael's current focus is launching Kisaco Research vendor product comparison reports with the new Kisaco Leadership Chart (KLC) analyst chart. The first KLC is also the first analyst chart in the AI chip industry, with 16 vendors having participated in the research.
In his career Michael worked at Rutherford Appleton Laboratory building simulators for electron and hole transport in semiconductors for UK national and European community research projects and published papers in learned journals. He then turned to building neural networks and created a startup selling his Prognostica Microsoft Excel add-in for time series forecasting, and wrote a book on the topic for publisher John Wiley & Sons in 1994.
Since 2003 Michael has worked as an IT industry analyst covering software engineering topics, from agile and DevOps, to application lifecycle management and cloud native computing. He started covering machine learning when deep learning emerged as the most recent wave of interest in AI and left his position as Distinguished Analyst at Ovum/Informa to join Kisaco Research and help build an analyst capability within the company.
My analyst coverage areas at KR Analysis
My first research project at KR was to create the first analyst comparison chart for AI chips. We invited AI chip producers to participate and were fortunate to have 16 vendors participate from across the globe: USA, UK, France, and China, and a mix of established players (Nvidia, Imagination, Intel, and Xilinx, to startups.
Our analysis showed that the market naturally fell into three areas of hot activity:
▪ Data centers and high-performance computing environments (HPC): here large boxes are installed and the aim is to achieve maximum performance for training and inferencing AI systems. The buyers are cloud hyperscalars, national research labs and agencies, and some large enterprises with big investments in AI.
▪ Small edge: the opposite end of the spectrum, building the smallest useful chip possible to sell as cheap as possible and embed in edge devices. AI is inferencing here.
▪ Automotive: an active industry in AI but highly regulated creating hurdles and technology adoption cadences that can be challenging for suppliers. AI is mainly inferencing here (for systems installed in vehicles).
We produced four Kisaco Leadership Charts out of this research.
We are also researching the machine learning (ML) software tools space, and our first report here is ML Lifecycle Solutions. The biggest challenge for enterprises is taking the research AI systems developed by their data scientist and deploying these into production at scale. Using a host of open source tools to achieve this is possible but time consuming to build and maintain, as well as prone to breakdown. This is why the ML lifecycle solution space exists.
Finally, in our first batch of KR Analysis reports we produced the KLC on engineering application lifecycle management (ALM) solutions. While ALM has been in existence as a distinct practice since KR Analysis and Michael Azoff introduction © Kisaco Research. All rights reserved. Unauthorized reproduction prohibited. 4 around 2003, it continues to evolve. We found the engineering and highly regulated industries relying on engineering and compliance oriented ALM to help manage risk and complexity.
Request a sample
Please complete the form below to receive a sample of this report.
Purchase the report
Company-wide Use | $3,999 | Buy Online
VAT will be added for companies based in the UK. For further information or support in purchasing a report, please contact email: [email protected]