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Quick Take: IBM Sues Micro Focus for Software Theft

Yesterday, IBM filed suit against Micro Focus for claims of copying part of the z/OS for data mapping in the web services implementation of Micro Focus Enterprise Suite. To understand this suit, I think the most relevant excerpts of claims in the suit are:

26. CICS® TS (Customer Information Control System Transaction Server) Web Services uses a “web service binding file,” known as a WSBIND file, to expose CICS® TS programs as web services and maps data received.

40. Micro Focus’s Enterprise Suite offers a web services implementation (“Micro Focus Web Services”) that includes a WSBIND file for mapping data
• Micro Focus’s WSBIND file uses IBM internal structures that are not available outside of IBM.
• The Micro Focus utility processing reflected in the log file exhibits the same configuration, program sequence, program elements, program optimizations, defects, and missing features as the corresponding CICS® TS utility programs.
• Micro Focus’s WSBIND file is encoded in EBCDIC—like IBM’s—yet, Micro Focus has no need for using that encoding as it uses an ASCII environment.

(Analyst’s note: I think this is probably going to be one of the key hinges of the lawsuit. EBCDIC is really an IBM-specific format at this point while ASCII is everywhere. A bit weird to use IBM’s specific encoding for characters.)

42. …no legitimate reason for Micro Focus to have copied IBM’s computer program. Without copying from IBM, Micro Focus had a broad range of design and architectural choices that would have allowed it to create software that offers the same features as the Micro Focus Enterprise Suite.

It’s no secret that IBM has bet the farm on modernization and digital transformation (see Red Hat). The ability to manage IBM customer technology evolution is core to the future of the business. If nothing else, this suit sends a strong message: Don’t Mess with the zSeries. I’m interested to see how this suit will reference Google vs. Oracle: this isn’t the same, but I’d imagine Micro Focus will try to make it sound that way.

Copy of complaint if you want to read the entire IBM legal complaint for yourself : https://filecache.mediaroom.com/mr5mr_ibmnewsroom/194536/Micro%20Focus%20Complaint.pdf

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November 11: From BI to AI (Anaconda, Coefficient, Databricks, dbt, Domino Data Lab, Matillion, Neo4J, PwC, Sagence, Snowflake, Tellius)

Editorial note: While Twitter and Meta aren’t precisely on the BI to AI spectrum per se, given the sheer prevalence and use of these massive data sources and the fast-moving news around layoffs and security issues for these properties lately, Amalgam Insights would recommend confirming that you are performing backups of relevant data on a regular schedule; that you are taking available security precautions including the use of two-factor authentication where possible; and that your communications strategies are nimble enough to respond to issues of impersonation. 

Funding and Finances

Coefficient Secures $18M Series A Funding Round

Spreadsheet data automation company Coefficient has raised an $18M A round. Battery Ventures led the funding round, with participation from existing investors Foundation Capital and S28 Capital. Coefficient will use the money to scale up global operations and expand its offerings.

Databricks Ventures Invests in Matillion

Strategic investment firm Databricks Ventures has taken an equity stake for an undisclosed sum in Databricks partner Matillion, a data integration solution. In doing so, Databricks extends their existing partnership with Matillion, providing financial support for Matillion’s Data Productivity cloud and how it works with Databricks’ Lakehouse Platform.

Updates and Launches

Tellius Improves User Experience and Ease of Visual Analysis with Version 4.0

Decision intelligence platform Tellius announced version 4.0 on Wednesday. Key new features include Multi-Business View Vizpads, allowing users to view and analyze across multiple data sources without needing to constantly switch between individual dashboards for each; an enhanced onboarding and ongoing user experience with walkthroughs and in-app chat; and more robust search functionality.

Neo4j Announces General Availability of its Next-Generation Graph Database Neo4j 5

Graph data platform Neo4J made Neo4J 5, the next version of its cloud-ready graph database, generally available earlier this week. Among the notable improvements: new syntax making complex queries easier to write; query performance improvements by up to 1000x; automatic scaleout to handle sudden massive bursts of query activity; and the debut of Neo4J Ops Manager to monitor and manage continuous updates across global deployments. 

Partnerships

Anaconda Will Integrate with Domino’s Enterprise MLOps Platform

Anaconda in Snowpark for Python Enters Public Preview

Anaconda made two partnership announcements this week. First, Anaconda is collaborating with Domino Data Lab to incorporate the Anaconda repository into Domino’s Enterprise MLOps Platform. Domino users will be able to access Anaconda’s Python and R packages without requiring a separate Anaconda enterprise license.

Second, Snowpark for Python, the Anaconda repository and package manager within Snowflake Data Cloud, has entered public preview. Snowflake users will be able to use Python to build data science workflows and data pipelines within Snowpark.  

On a related note, dbt Labs also announced support for data transformation in Python to dbt, allowing dbt customers to take advantage of Python capabilities on major cloud data platforms such as Snowflake. Joint dbt and Snowflake customers will be able to use Python capabilities for both analytics and data science projects on Snowpark.

Acquisitions

PwC Acquires Data Strategy Consulting Firm Sagence 

Data management and analytics consulting firm Sagence has been acquired by PwC, adding to PwC’s existing data strategy and digital transformation capabilities. Sagence provides additional expertise and experience in creating action plans for proposed data strategies.


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November 4: From BI to AI (Alation, Cloudera, Collibra, IBM, Informatica, Qlik)

Funding

Alation Raises $123M Series E

Enterprise data intelligence platform Alation announced a $123M Series E round of funding this week. Thoma Bravo, Sanabil Investments, and Costanoa Ventures led the round, with additional participation from new investor Databricks Ventures and existing investors Dell Technologies Capital, Hewlett Packard Enterprise, Icon Ventures, Queensland Investment Corporation, Riverwood Capital, Salesforce Ventures, Sapphire Ventures, and Union Grove. Alation will use the capital to continue accelerating product innovation and global expansion.

Partnerships

Cloudera Expands Partner Opportunities, Accelerates Go to Market

On November 2, Cloudera debuted the Cloudera Partner Network, redesigning their existing partner program’s approach. CPN members will see improved tools for supporting go-to-market initiatives, a FastTrack Onboarding Program to shorten time-to-market capabilities, programs for rebates and market development funds to demonstrate financial commitment, a Partner Success Team to improve training, and additional benefits to support the new CDP One SaaS solution.

Launches and Updates

Collibra Announces Updates to Collibra Data Intelligence Cloud

At Data Citizens ’22, Collibra announced new capabilities for Collibra Data Intelligence Cloud. A new data marketplace will make it faster and easier to find curated and approved data, speeding up decision making and action. The Workflow Designer, now in beta, will help teams automate business processes in creating new workflows, and usage analytics will show which assets are most widely and frequently used. On the compliance side, Collibra also released Collibra Protect, available through their Snowflake partnership, to provide greater insight into how protected and sensitive data is being used, as well as protect said data and maintain compliance.   Collibra Data Quality and Observability, when deployed in an organization’s cloud, will help organizations scale and secure their data quality operations.

IBM Announces IBM Business Analytics Enterprise  

On November 3, IBM launched IBM Business Analytics Enterprise, a new suite that includes business intelligence planning, budgeting, reporting, forecasting, and dashboarding capabilities. Among the key new features is the IBM Analytics Content Hub, which will let users assemble planning and analytics dashboards from a number of vendor sources. In addition, the Hub tracks and analyzing usage patterns to recommend role-based content to users.

Up Next for Informatica: Intelligent Data Management Cloud for State and Local Government 

Informatica released the State and Local Government version of their Intelligent Data Management Cloud this week. This continued expansion of vertical-specific IDMCs demonstrates Informatica’s commitment to serving a variety of government clients beyond just the federal.

Qlik Launches Real-Time Enterprise Data Fabric Qlik Cloud Data Integration

Qlik released Qlik Cloud Data Integration, a set of SaaS services that form a data fabric. Among the major cloud platforms QCDI will integrate with are AWS, Databricks, Google Cloud, Microsoft Azure Synapse, and Snowflake. Data from these sources will be sent through QCDI, where it can be transformed from its raw state to analytics-ready, allowing for automated workflows for apps and APIs while accounting for metadata management and lineage.

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October 28: From BI to AI (Amazon Web Services, Axelera AI, Bloomberg, data.world, Informatica, IBM, LatticeFlow, Microsoft, OpenAI, Shutterstock, ThoughtSpot)

Funding and Finance

Edge AI Company Axelera AI Announces $27M Series A

Edge AI startup Axelera AI closed a $27M Series A funding round this week. Innovation Industries led the round, with participation from imec.xpand and SFPI-FPIM. Axelera AI will use the funding for launching and producing its AI acceleration platform, as well as hiring.

LatticeFlow Claims $12M in Series A Funding

AI platform LatticeFlow secured $12M in Series A funding. Atlantic Bridge and OpenOcean led the funding round, with participation from new investors FPV Ventures and existing investors btov Partners and Global Founders Capital. The funding will go towards expanding LatticeFlow’s capacity to diagnose and repair errors in AI data and models,

OpenAI Invests Tens of Millions of Dollars in Audio and Video Editing App Descript

AI company OpenAI, most recently in the news for its AI text and image generators, is investing tens of millions of dollars in audio and video editing app Descript at a valuation of $550M. Between this, the recent expansion of its partnership with content platform Shutterstock, and more money potentially flowing OpenAI’s way from Microsoft, OpenAI is making moves to secure its position in modern AI-based content creation.

Launches and Updates

AWS Releases Amazon Neptune Serverless 

AWS announced Amazon Neptune Serverless, a serverless version of their graph database service which automatically provisions and scales resources for unpredictable graph database workloads. Amazon Neptune Serverless is available today to AWS customers running Neptune in specific regions; availability in other regions is coming soon.

Bloomberg Carbon Emissions Dataset Now Covers 100,000 Companies

Bloomberg announced that it had enlarged its carbon emissions dataset to cover 100,000 companies. The dataset includes company-reported carbon data, as well as Bloomberg-generated estimates of carbon data for companies that do not have or provide carbon emissions data, and accompanying data reliability scores.

Informatica Launches Intelligent Data Management Cloud for Higher Education

Adding to their collection of vertical-specific releases of its Intelligent Data Management Cloud, Informatica launched their Intelligent Data Management Cloud for higher education this week. IDMC helps integrate educational data from a wide variety of decentralized sources while ensuring data remains secure and compliance and privacy standards are respected.

IBM Adds Natural Language Processing, Text to Speech, Speech to Text Libraries to Embeddable AI Portfolio

IBM released three new libraries this week, expanding their embeddable AI portfolio. These libraries include IBM Watson Natural Language Processing Library, IBM Watson Text to Speech Library, and IBM Watson Text to Speech Library. IBM Ecosystem partners will be able to use these libraries to develop and scale AI apps more quickly. 

ThoughtSpot for Sheets Brings Self-Service Analytics to Google Sheets

Analytics company ThoughtSpot debuted ThoughtSpot for Sheets, a web plugin for Google Sheets. Users will be able to install and run ThoughtSpot for Sheets directly in their web browser, capable of analyzing the data available in their Google Sheets spreadsheets while minimizing the technical knowledge necessary to do so. ThoughtSpot will be compatible with additional partners in the near future.

Hiring

data.world Names New CMO, SVP of Sales, VP of Finance

Enterprise data catalog company data.world made several hiring announcements this week. New Chief Marketing Officer Stephanie McReynolds joined data.world from Ambient.ai, where she served as head of marketing. Prior to that, McReynolds was the SVP of Marketing and first marketing executive at fellow data catalog company Alation. New SVP of Sales Richard Yonkers came to data.world from Knoema, an enterprise data hub provider, where he served as the senior vice president of sales. Mineo Sakan was the VP of Global Finance at data protection firm HYCU prior to joining data.world as their new VP of Finance.

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October 21: From BI to AI (Alteryx, Bloomberg, Dataiku, Google Cloud, Oracle, Stability AI, Tableau, Tellius, TigerGraph)

Oracle CloudWorld Announcements

Oracle made a number of announcements at Oracle CloudWorld this week.

Oracle Database 23c Now in Beta
Version 23c of Oracle Database, code named “App Simple,” is now available in beta. As highlighted by the code name, improvements focused on simplifying application development, particularly for apps written using JSON, Graph, or microservices. JSON Relational Duality is Oracle’s new approach to allow data to be simultaneously used and understood as both app-friendly JSON documents and as database-friendly relational tables, allowing JSON app data to be directly queried.

Oracle Launches MySQL HeatWave Lakehouse
Oracle expanded the MySQL HeatWave portfolio with the addition of MySQL HeatWave Lakehouse, which will allow customers to process and query data in object store at multi-terabyte scale. This will directly compete with Redshift and Snowflake in providing a cost-efficient, performant lakehouse offering.

Oracle Innovates Across Data and Analytics Portfolio
Oracle also announced product innovations across its data and analytics portfolio. Oracle Analytics Cloud added a semantic modeler to present the semantic model to business users in an appropriate manner; advanced composite visualizations to organize content and present data patterns and signals in a more easily understood manner; one-click automated insights that provide recommendations for visualizations; and AI and ML enhancements to connect Oracle Cloud Infrastructure cognitive services to Oracle Analytics Cloud. Oracle Fusion Analytics improved their existing ERP, SCM, and HCM analytics solutions with vertical-specific enhancements, and added Oracle Fusion CX Analytics to the OFA portfolio to give sales, marketing, service, and finance users KPIs and dashboards.

Oracle and NVIDIA Team Up to Accelerate Enterprise AI Adoption
Finally, Oracle and NVIDIA announced a partnership that will bring NVIDIA’s complete accelerated computing stack, including tens of thousands of GPUs, to Oracle Cloud Infrastructure to permit AI training and deep learning inference at scale.

Funding

Stability AI Announces $101M Seed Round
Open source AI company Stability AI announced a $101M seed round at a nearly $900M valuation. Coatue, Lightspeed Venture Partners, and O’Shaughnessy Ventures LLC led the round. Stability AI will use the funding to speed up the development of open AI models across a wide variety of use cases, consumer and enterprise alike.

Tellius Raises $16M B Round
AI decision intelligence platform Tellius announced a $16M B round of funding, announced October 20. Baird Capital led the round, and all existing investors also participated: Grotech Ventures, Sands Capital Ventures, and Veraz Investments. Tellius will use the funding to expand go-to-market, hire across sales, marketing, and product engineering, and R+D for their platform.

Launches and Updates

Alteryx Announces New Analytics Cloud Capabilities, Version 22.3
At Inspire EMEA 2022, Alteryx announced the 22.3 Alteryx product release, and additional enhancements to Alteryx Analytics Cloud. Alteryx Machine Learning is now running on Alteryx Analytics Cloud, and Designer Cloud has improved Snowflake data processing performance when moving from AWS. As for Alteryx 22.3, Alteryx’s Data Connection Manager supports Azure Active Directory group authentication for Databricks and Snowflake, and integrations with third-party vaults like CyberArk and HashiCorp. 22.3 also features enhanced Google BigQuery connectivity and performance improvements.

Bloomberg Data License Content Now Available on Google Cloud
Bloomberg made its Data License content available on Google Cloud. Clients will be able to integrate this cloud data into their Google Cloud-specific workloads directly.

Tableau Launches Version 2022.3
Tableau announced version 2022.3 this week. Key new features include a Data Guide guided experience to Tableau, Table Extensions that will let customers enrich their data with advanced analytics and predictions, and adding “dynamic zone visibility” functionality to dashboards, allowing users to see only the dashboard contents that are relevant without needing to manually design multiple individual dashboards.

TigerGraph Will Support openCypher in GSQL.
TigerGraph announced this week that they would support the openCypher query language in TigerGraph’s own graph query language. Providing this support will make it easier for developers to build or migrate graph applications to TigerGraph databases.

Partnerships

Dataiku and Slalom Team Up on AI Strategy
Dataiku announced a partnership with Slalom, a global consulting firm. Slalom will provide strategic guidance to Dataiku enterprise customers on implementing AI and MLOps projects.

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Cloud Cost Management Vendor Profile: IBM Turbonomic

Amalgam Insights continues to present its list of Distinguished Vendors for Cloud Cost and Optimization Management. This matters because analysts assessed nearly 30 providers for this effort; only a third were able to demonstrate genuine differentiators and approaches that satisfied Amalgam Insights’ requirements for achieving Distinguished Vendor status. To that point, we already have posted profiles on SADA, Spot by NetApp, Apptio Cloudability, Yotascale, Kion, and CAST AI . We next discuss IBM Turbonomic.

WHY IBM TURBONOMIC FOR CLOUD COST AND OPTIMIZATION MANAGEMENT

  • Focus on application performance, which leads to savings
  • Platform configuration is automated, saving IT time and effort during deployment
  • Software learns from organizations’ actions, so recommendations improve over time

ABOUT IBM TURBONOMIC

IBM Turbonomic is an Amalgam Insights Distinguished Vendor for Cloud Cost and Optimization Management. Founded in 2009, Turbonomic was acquired by IBM in 2021. IBM Turbonomic now acts as Big Blue’s solution to ensure application performance and governance across cloud environments, including public and private. Turbonomic has two offices in the United States — its headquarters in Boston and a satellite location in Newark, Delaware — as well as one in the UK and another in Canada. IBM does not publicly disclose how many Turbonomic employees it has, nor does it break out Turbonomic annual revenue or provide customer retention rates.

In terms of cloud spend under management, Turbonomic states that it does not track the amount of money its clients spend on cloud computing. Turbonomic serves Fortune 2000 customers across industries including finance, insurance, and healthcare. Turbonomic is typically considered by organizations that have at least 1,000 cloud instances or virtual machines; many support tens of thousands.

IBM TURBONOMIC’S OFFERING

IBM Turbonomic Application Resource Management targets application performance and governance throughout an organization’s cloud environment, which can include public cloud (Amazon Web Services, Microsoft Azure, Google Cloud), private cloud (IBM, VMware), and multi-cloud environments.

The platform optimizes cloud computing, storage, database as a service, reserved instances, and Kubernetes, but does not currently address spot instances). Furthermore, it optimizes and scales based on IOPs (input/output), reservations, and discounts. Overall, IBM Turbonomic aims to ensure spend aligns to applications, preventing cost overruns and keeping applications performing optimally. While Turbonomic mainly serves IT users, Turbonomic recently teamed with Flexera to add a detailed cost-reporting module that appeals to Financial Operations (FinOps) experts.

IBM Turbonomic charges for its cloud application optimization software based on the number of resources under management. Rather than offering individual add-on capabilities, IBM Turbonomic lets clients choose more advanced capabilities by buying different licensing tiers associated with integrations to other software and processes such as IT service management, orchestrators, and application performance management. IBM Turbonomic includes technical support with all tiers. IBM Turbonomic and its third-party channel partners offer professional services as needed.

IBM Turbonomic states that its top differentiator originates from artificial intelligence that matches application demand to underlying infrastructure supply at every layer of the stack continuously in real-time with automatable resourcing decisions. As more organizations use IBM Turbonomic, the automated recommendations provided to all of its customers improve. Cloud administrators gain insight into suggested actions, such as investments to enhance performance and save money.

IBM Turbonomic Application Resource Management is delivered as software-as-a-service. It works across public, private, containerized, and bare metal cloud environments. IBM Turbonomic’s reference customers include Providence Health, which has 120,000 employees; Litehouse Foods, which makes salad dressing, cheese, and other foods; and apparel maker Carhartt.

COMPETITION AND COMPETITIVE POSITIONING

IBM Turbonomic mainly competes against organizations’ in-house spreadsheets and mix of tools that are specific to the technologies in use. In these cases, IBM Turbonomic finds that organizations are over-provisioning cloud computing resources in the hopes of mitigating risk. Therefore, they are spending too much and only addressing application performance when something goes wrong.

IBM Turbonomic also often faces VMware CloudHealth in its prospective deals.

IBM Turbonomic states that it draws customers because of automation and recommendations that tend to result in the following business outcomes:

  • Reduction of public cloud spend by 30%
  • Increase in team productivity by 35%
  • Improvement of application performance by 20%
  • Increase in speed to market by 40%

IBM TURBONOMIC’S PLANS FOR THE FUTURE

IBM Turbonomic keeps its roadmap private, so details about upcoming enhancements are not public. However, Amalgam Insights believes that IBM Turbonomic will pursue improvements in sustainability reporting and GitOps resizing in the near future, and may soon pursue a deeper relationship with Microsoft Azure, given that three of these areas are of interest to IBM Turbonomic’s current client base.

AMALGAM INSIGHTS RECOMMENDATIONS

Amalgam Insights recommends that organizations with a minimum of 1,000 cloud instances or virtual machines, and residing within the Fortune 2000, consider IBM Turbonomic Application Resource Management.

Because the platform automatically configures during deployment, provides ongoing recommendations for application and cloud-configuration improvement, and continues to learn from users’ actions, organizations can observe how cloud environments are continuously optimized. This allows IT teams to support cloud consumption needs while also ensuring the organization does not overpay or underresource. In addition, FinOps professionals gain the information they need to track and budget digital transformation efforts without burdening their IT counterparts.

Combined, these capabilities are critical to organizations’ goals of delivering stewardship over their cloud environments while maintaining fiscal responsibility that best serves shareholders, investors, and staff.


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Cloud Cost Management Vendor Profile: CAST AI

Cast AI - Amalgam Insights' 2022 Distinguished Vendor for Cloud Cost Management

Managing cloud infrastructure is no easy task, especially when containers such as Kubernetes come into play. In our ongoing effort to help organizations understand what they need to do to make the most of their cloud environments, Amalgam Insights this year briefed with a number of management and optimization vendors. We continue to publish our findings, which include analyst guidance complete with a series of vendor profiles. This installment focuses on CAST AI, a company that takes a different approach to cloud cost and optimization management by homing in on containers. Read on to learn why that is so important and to understand Amalgam Insights’ resulting recommendations for enterprises.

WHY CAST AI FOR COST CLOUD COST AND OPTIMIZATION MANAGEMENT

  • Optimizes Kubernetes containers on a continuous basis
  • Company claims to save users an average of 63% on cloud bills
  • Cost reporting and cluster analysis provided as a free service

ABOUT CAST AI

CAST AI is an Amalgam Insights Distinguished Vendor for Cloud Cost and Optimization Management. Founded in 2019, Miami-headquartered CAST AI employs 60 people in Florida and Lithuania. It raised $10 million in Series A funding in fall of 2021, following its $7.7 million seed round in late 2020. CAST AI does not look for a specific customer size; some of its users have fewer than two dozen virtual machines, while others run thousands. The privately held firm does not disclose annual revenue or how much cloud spend it manages.

CAST AI’S OFFERING

CAST AI automates and optimizes Kubernetes environments on Amazon Web Services (AWS) Elastic Kubernetes Service, kOps running on AWS, Microsoft Azure Kubernetes Service, and Google Cloud Platform Google Kubernetes Service as well as Kubernetes clusters running directly on CAST AI.

Cast AI users — who typically are DevOps (Development Operations) experts — may run cost reporting that includes cluster analysis and recommendations. FinOps (Financial Operations) professionals can take the reporting results and incorporate them into their practices.

The CAST AI engine goes beyond cost reporting to rearrange Kubernetes environments for the most effective outcomes. To do this, CAST AI connects to a specified app, then runs a script that installs agents to collect information about the app. After that, a report pops up that can provide recommendations for reducing the number of Kubernetes machines or changing to a different compute platform with less memory, all to cut down on cost.

If a user accepts CAST AI’s recommendations, he or she can click a button to optimize the environment in real time. This button sets off a continuous optimization function to give orders to Amazon Elastic Kubernetes Service (EKS), Google Kubernetes Engine (GKE), or Azure Kubernetes Service (AKS) to rearrange itself, such as autoscaling in real time and rebalancing clusters. Users set their desired automation and alerting thresholds. CAST AI pings the app every 15 seconds and produces an hourly graph. CAST AI claims its users save an average of 63% on their cloud bills.

Pricing for CAST AI varies. CAST AI does not enforce a minimum spend requirement. Rather, it charges by the number of active, optimized CPUs. That starts at $5 per CPU per month and there are tiered discounts from 1-5,000 CPUs, then 5,001-15,000, and so on. Base subscriptions start at $200 per month and go up to $5,000 per month or more, depending on volume discounts. CAST AI provides cost reporting and cluster analysis for free, with no time limits. Users also can buy cost management as a standalone service.

COMPETITION AND COMPETITIVE POSITIONING

CAST AI competes most frequently against the Ocean platform from Spot by NetApp in competitive deals. For the most part, though, CAST AI “competes” against DevOps professionals trying to reduce cloud costs manually — a difficult and time-consuming effort.

CAST AI finds that it gains customers because of its engine’s ease of use and ability to make changes in real-time. This further frees DevOps experts to focus on innovative projects.

CAST AI goes to market via its website and, in Europe, Asia, and the United States, also through third-party partners.

CAST AI’s reference customers including La Fourche, a French online retailer of organic products, and ecommerce consultancy Snow Commerce.

CAST AI’S PLANS FOR THE FUTURE

CAST AI plans to build an air-gapped version of its engine disconnected from the Internet and fully supported within the customer’s internal environment for private cloud users in vertical markets including government and banking. Because CAST AI collects metadata to optimize Kubernetes environments, CAST AI is working on this capability to support more governed industries and organizations.

AMALGAM INSIGHTS’ RECOMMENDATIONS

Amalgam Insights recommends that organizations with Kubernetes containers try CAST AI’s free trial to understand how the platform might help save money and optimize resources. Although Kubernetes has largely won as the software container of choice in DevOps environments, businesses still have not standardized on strategies to optimize the compute and storage associated with containerized workloads and services. Amalgam Insights believes that Kubernetes optimization should not be a long-term direct responsibility for developers and architects as tools emerge to define the resources that are most appropriate for running containerized applications at any given time.

Organizations worldwide are struggling to control cloud costs, especially as they pursue containerization and cloud refactorization projects associated with digital transformation. Organizations also are cleaning up pandemic-spurred cloud deployments that quickly got out of hand and have proven difficult to keep in line since then. CAST AI’s technology provides an option that DevOps engineers should consider as they seek to tighten and optimize the spend tied to applications containerized in the cloud.

Need More Guidance Now?

Check out Amalgam Insights’ new Vendor SmartList report, Control Your Cloud: Selecting Cloud Cost Management in the Face of Recession, available for purchase. If you want to discuss your Cloud Cost Management challenges, please feel free to schedule time with us.

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Cloud Cost Management Vendor Profile: Kion

Organizations juggling services from the major public cloud providers — Amazon Web Services, Microsoft Azure, and Google Cloud Platform — often struggle to streamline the disparate data that emerge. For businesses and government agencies with a deliberate focus on financial management, Kion can prove a management option to consider.

In Amalgam Insights’ latest profile featuring cloud cost management and optimization vendors, we discuss what Kion does and how the company differs from its competition.

WHY KION FOR CLOUD COST AND OPTIMIZATION MANAGEMENT

  • Single-platform approach for identity and access management, financial control, and security configuration across the top three public cloud platforms
  • Deep emphasis on compliance checks, including United States federal government compliance
  • Insight into financial management beyond spend savings to include budgeting, forecasting, and compliance

ABOUT KION

Kion is an Amalgam Insights Distinguished Vendor for Cloud Cost and Optimization Management. Formerly known as cloudtamer.io, Kion was founded in 2018. While it is headquartered in Fulton, Maryland, Kion takes a remote-first approach to employment, so it has staff across the United States — more than 50 people as of May 2022. Kion reports annual revenue of between $5 million and $10 million and holds a Net Promoter Score of 81. The company serves about 45 clients collectively spending more than $500 million across IaaS and PaaS.

Most of Kion’s customers fall into three segments: government, higher education, and commercial enterprise. For the government and higher education markets, Kion helps agencies manage funding allocations, align spend with appropriations, meet standards, and ensure compliance (e.g. FedRAMP, NIST SP 800-171, CMMC). Enterprises tend to look to Kion for help in improving the engineer experience to accelerate cloud adoption.

KION’S OFFERING

Kion calls its approach to cloud governance and management “cloud enablement.” This term is intended to describe a combination of automation and orchestration, financial management, and ongoing compliance checks to gain visibility into and control over multiple clouds. 

Kion installs in the customer’s cloud account rather than as a software-as-a-service solution. Kion supports management across cloud providers and lets users integrate with identity access management tools including Okta, native Active Directory, and OneLogin; with IT service management platforms including ServiceNow, Jira, and Splunk; and with host-level vulnerability management technologies including Tenable.

Kion’s platform provides capabilities for automation and orchestration, financial management (FinOps), and continuous compliance, including self-service provisioning for use governance. For financial management, Kion users can allocate funds, receive alerts on potential budget overruns, and proactively remediate cost issues. Kion’s compliance measures contain auto-remediation for governance policy issues, as well. Kion assesses factors such as budget and funding sources to show what remains in a budget, and where that money came from to align cost management, budgeting, and forecasting. Kion’s compliance capabilities enforce policies across clouds at project and resource levels. Kion supports more than 4,500 compliance checks and provides a security control matrix that displays how cloud layers are meeting requirements.

Admins can enforce budget actions that prevent overspending in DevOps and sandbox environments. Kion pulls in data from multiple sources to auto-populate fields.

Standard support for Kion includes email with a two-business-day response time, and access to the Kion Support Center. Customers may procure annual premium support to have a dedicated technical account manager.

Kion’s pricing depends on cloud spend under management. The company sells directly through its in-house sales teams, third-party partners, and on cloud marketplaces. Kion also provides a back-end platform which can be white-labeled to support managed service providers, resellers, and system integrators.

COMPETITION AND COMPETITIVE POSITIONING

Kion wins customers based on several operational challenges. First, it attracts users who struggle to move into the cloud quickly. Second, Kion appeals to organizations struggling with cloud spend excesses, wasted resources, and security concerns. Third, Kion lands users lacking preventive controls. Finally, the company gets new business from companies seeking to remove complexity as they provision new cloud accounts and projects.

Kion competes most often against internal processes or homegrown tools. It also competes against Spot by NetApp and CloudHealth by VMware in the financial reporting realm. On the security end, Kion faces Fugue and Turbot in competitive deals. Some organizations view Kion as a platform that integrates those products (and others), or as a tool that will eventually replace those other brands. Rather than bifurcate personas into specific operational responsibilities — say, by FinOps, SecOps, and DevOps — Kion aligns with business personas and role-based governance across the platform based on functional need and to control spend.

Kion states that customers see savings of at least 30 percent through savings opportunities and cost optimizations. With automation, Kion claims soft-dollar savings can exceed 60 percent if organizations are willing to also review staffing, process, and policy decisions. Kion’s reference customers include NASA, Indeed, the Centers for Medicare & Medicaid Services, and Encamp.

KION’S PLANS FOR THE FUTURE

Kion plans to build more contextual insight to display cloud environment behaviors that are interrelated so users can make more informed decisions. Kion also intends to add more compliance policies as well as cloud platforms beyond the Big Three of Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

AMALGAM INSIGHTS’ RECOMMENDATIONS

Amalgam Insights recommends that organizations — particularly in government, higher education, and commercial enterprise — trying to manage one or more of the top three public cloud providers consider Kion. Kion focuses on ease-of-use and cross-departmental visibility to avoid overspending and ensure security and compliance. That streamlined approach provides a single view for cloud cost and optimization management, budgeting, and technology implementation. Amalgam Insights recommends Kion for companies that seek to cut cloud costs and consider financial management to be part of a greater effort of improving operational performance associated with cloud services.

Need More Guidance Now?

Check out Amalgam Insights’ new Vendor SmartList report, Control Your Cloud: Selecting Cloud Cost Management in the Face of Recession, available for purchase. If you want to discuss your Cloud Cost Management challenges, please feel free to schedule time with us.

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October 7: From BI to AI (Apollo GraphQL, AWS, CelerData, Domino Data Lab, Komprise, Kyndryl, SingleStore, Teradata)

Funding

SingleStore Closes Additional $30M in Series F Funding, Total Now at $146M

Database company SingleStore closed an additional $30M in F-round funding earlier this week, with Prosperity7 as a new investor. This additional investment brings SingleStore’s total for their F round up to $146M, after an initial round in September 2021 for $80M and an additional $36M in July 2022. In the interim, SingleStore has doubled its headcount, with geographic expansions to Ireland, Singapore, and Australia, and hiring continues.

Updates

Apollo GraphQL Launches GraphOS to Scale “Supergraphs”

On October 5, Apollo GraphQL debuted Apollo GraphOS. GraphOS is a platform to build, connect, and scale “supergraphs,” which are themselves architectures that bring together a company’s data, micro services, and other digital capabilities into one network to simplify data access and sourcing for app building. Key features of GraphOS include providing a centralized updated repository for schemas and pipelines, new GraphQL capabilities such as live queries and edge caching,  both cloud and self-hosting options, and security and governance capabilities to control who can access your supergraphs when and why

CelerData Launches Quick Start for StarRocks on Amazon Web Services 

On October 6, analytics platform CelerData released AWS QuickStart for StarRocks. This release deploys StarRocks on the AWS cloud, supporting quick deployment of real-time analytics and providing high concurrency while guiding users to follow AWS best practices

Domino 5.3 Previews Nexus Hybrid and Multi-Cloud Capabilities
Domino Data Lab released version 5.3 of their Enterprise MLOps platform yesterday. Key features include a private preview of Domino’s Nexus hybrid and multi-cloud capabilities, announced back in June; additional data connectors for Amazon S3 tabular data, Teradata warehouses, and Trino; and GPU-based model inference capabilities extended beyond model training to model deployment, helping bring complex models based on deep learning capabilities into production. Domino 5.3 is generally available now; companies who would like to preview Nexus can request access on the Domino Nexus website.

Komprise Rolls Out Fall 2022 Release 

Unstructured data management company Komprise released the Fall 2022 version of Komprise Intelligent Data Management. New capabilities include Komprise Smart Data Workflows, which let IT teams automate key parts of the data tagging and discovery process; and Deep Analytics, which permits authorized users outside of IT to view certain characteristics of their data and work with IT for better data management.

Partnerships

Kyndryl and Teradata Team Up for Cloud Migration
IT infrastructure services provider Kyndryl and data platform Teradata announced a strategic partnership earlier this week. The companies will combine Kyndryl’s data and AI services and Teradata’s cloud analytics and data platform to help customers migrate from on-prem data warehouses to the cloud.

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September 30: From BI to AI (AWS, Databricks, DataRobot, Domino, Microsoft Azure, Qlik, Salesforce, SAS) 

Dreamforce

Salesforce Premieres Genie, the New Realtime Data Platform Behind the Customer 360 

At Dreamforce, Salesforce launched Salesforce Genie, a realtime data platform undergirding Salesforce Customer 360. Genie ingests and stores streams of realtime data and combines it with transactional Salesforce data, then turns the combined data into a unified customer record. In addition, Einstein AI can provide additional relevant personalizations and predictions based on this realtime data, and Flow can trigger actions automatically based on the same realtime data. 

Salesforce and AWS Now Let You “Bring Your Own AI” to Customer 360 

Salesforce and AWS teamed up to reveal new integrations between Salesforce and Amazon SageMaker. Joint customers will be able to use SageMaker and Einstein AU in concert to build custom AI models – to “bring your own AI” and use it in realtime across the Customer 360. Cleansed and unified realtime Salesforce customer data alongside an organization’s data from an AWS data lake or data warehouse will be jointly accessible for building and training machine learning models in SageMaker.  The underlying technology enabling these integrations is Salesforce Genie, mentioned above.

Salesforce Appoints Robin Washington Lead Independent Director of the Board 

Salesforce also announced the appointment of Robin Washington as the Lead Independent Director of the Company’s Board of Directors, succeeding Sanford Robinson. Washington has served as Director of Salesforce since 2013, and currently also chairs the Board’s Audit Committee. Washington has also served on the boards of Gilead Sciences, and currently serves on the boards of Alphabet, Honeywell International, and Vertiv Holdings Co. 

Launches and Updates

DataRobot Debuts Dedicated Managed AI Cloud

DataRobot Dedicated Managed AI Cloud is now publicly available, DataRobot announced earlier this week. The Dedicated Managed AI Cloud is a dedicated hosted version of DataRobot’s AI Cloud, managed by DataRobot experts, allowing organizations to outsource certain aspects of AI platform deployment, configuration, management, and maintenance when staffing constraints limit on-prem capabilities.

Domino Data Lab Announces New Ecosystem Solutions with NVIDIA

Domino Data Lab announced two solutions with NVIDIA ecosystem partners last week. Domino and NVIDIA have created an on-prem GPU reference architecture and an integrated MLOps solution for high-performance processing needs on NVIDIA DGX systems.

Partnerships

Qlik Launches Two More Products in Partnership with Databricks  

Qlik debuted two more solutions in its partnership with Databricks. The first is the launch of the Databricks Lakehouse (Delta) Endpoint within Qlik Data Integration, which will make it easier for customers to get data into their Delta Lakehouse. The second is the integration of Qlik Cloud with Databricks Partner Connect, improving the “trial experience” of Qlik Data Analytics within Databricks. 

SAS Viya Now Available On Azure Marketplace

SAS Viya is now available on the Microsoft Azure Marketplace, expanding on the existing SAS-Microsoft partnership. Users will be able to access the full Viya package on Azure, including SAS Visual Analytics, SAS Visual Statistics, SAS Visual Data Mining and Machine Learning, and SAS Model Manager, with no-code and code-centric interfaces available.

Hiring

 Debanjan Saha Named Chief Executive Officer of DataRobot

Last week, DataRobot announced that Debanjan Saha had been appointed as Chief Executive Officer. Saha originally joined DataRobot in February 2022 as President and Chief Operating Officer, and served as DataRobot’s interim CEO when Dan Wright stepped down in July. Prior to DataRobot, Saha was the VP/GM of Data Analytics at Google, and the VP GM of Aurora and RDS at Amazon.