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Salesforce Heroku
09Dec

Salesforce Modernizes Heroku

Salesforce Modernizes Heroku PaaS with Kubernetes, .NET, and More Salesforce is rolling out a significant upgrade to Heroku, its popular Platform-as-a-Service (PaaS), to better align with modern developer needs. Key enhancements include support for Amazon Elastic Container Registry (ECR), AWS Global Accelerator, Elastic Kubernetes Service (EKS), AWS Graviton processors, and AWS Bedrock. The revamped platform, dubbed the Heroku Next Generation Platform, was unveiled at the AWS Re:Invent 2024 conference. While some features are in public beta, Salesforce plans to fully release additional capabilities by 2025. Catering to the Modern DeveloperHeroku’s overhaul reflects the growing dominance of Kubernetes and the increasing demand for AI-enabled applications, including autonomous ones built in Salesforce’s Agentforce. Rebecca Wettemann, founder of Valoir, notes that these trends required Salesforce to evolve Heroku to remain competitive in the PaaS market. Kubernetes, for instance, is widely used for app containerization across clouds, while AI applications are becoming a focal point for many developers. “The update broadens Heroku’s appeal to developers who rely on Kubernetes or are building AI applications,” Wettemann said. Another notable addition is support for open telemetry, a standardized approach to monitoring app performance. Developers can now stream real-time metrics such as app health and container logs into their preferred visualization tools. “This integration offers unparalleled flexibility for our customers to work with a wide ecosystem of telemetry collectors,” said Gail Frederick, Heroku’s CTO at Salesforce. Introducing .NET SupportOne of the standout updates is the inclusion of .NET, a widely used open-source framework. Developers can now use .NET languages such as C#, F#, and Visual Basic alongside Heroku’s existing support for languages like Python, Ruby, Java, Node.js, and Scala. This strategic move aligns Heroku with a broader audience, especially developers familiar with Microsoft’s ecosystem. “Heroku is all about developer choice,” said Frederick. “Adding .NET ensures we continue to serve diverse needs.” Streamlining Development and DeploymentHeroku aims to simplify app development by automating infrastructure management and lifecycle tasks. “Heroku is the platform developers turn to when they need things to work without thinking about infrastructure,” said Adam Zimman, Senior Director of Product Marketing at Heroku. The platform abstracts complex deployment steps, such as configuration, provisioning, and autoscaling, enabling developers to focus on coding and innovation. Apps are deployed as pre-packaged “slugs” that run on Heroku’s dynos, isolated Unix-based containers. Developers can scale their apps dynamically by adding or removing dynos via the platform’s management interface. Efficiency Gains for BusinessesZimman highlighted the efficiency benefits of Heroku’s approach, projecting up to a 40% boost in developer productivity and a 30% reduction in developer expenses. “By taking care of the heavy lifting, we enable businesses to deliver applications faster and more cost-effectively,” he explained. Heroku also offers over 500 pre-built add-ons and build packs, covering functions like messaging, database management, and email services. These integrations provide additional flexibility and speed up the development lifecycle. Scaling Beyond StartupsWhile Heroku is often associated with startups, Salesforce has scaled the platform to accommodate enterprise-grade applications. “Heroku now evolves with your business,” said Chris Peterson, Senior Director of Product Management at Heroku. The platform has powered over 13 million applications and 38 million managed data stores since its launch in 2007. Many Salesforce applications also run on Heroku, leveraging deep integrations to extend the Salesforce ecosystem seamlessly. Heroku’s pricing starts at $7 per month for a basic plan and scales up to $40,000 per month for enterprise-grade solutions, ensuring it meets the needs of organizations of all sizes. With these updates, Heroku continues to position itself as a go-to platform for developers, enabling faster time-to-market, reduced operational complexity, and a better overall development experience. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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December 9, 2024in Data, Enterprise0 Comments
Veeam Latest Acquisition
08Oct

Veeam Latest Acquisition

Veeam continues its acquisition strategy with the purchase of Alcion, bolstering its capabilities in AI and as-a-service offerings. This acquisition follows Veeam’s investment in Microsoft 365 backup-as-a-service provider Alcion last year, and brings in a team of AI and security specialists. Analysts and Veeam executives see this move as a key step in expanding Veeam’s as-a-service offerings. Earlier this year, the company launched Veeam Data Cloud, a backup-as-a-service solution for Microsoft 365 and Azure workloads. “After years of resisting, Veeam has fully embraced the as-a-service model,” said Christophe Bertrand, an analyst at TheCube Research. Veeam Latest Acquisition The acquisition, which closed in mid-September, marks the second time Veeam has purchased a company founded by Niraj Tolia and Vaibhav Kamra. In 2020, Veeam acquired Kasten, their Kubernetes backup provider. A year ago, Veeam led a million funding round for Alcion, which has since developed AI-driven data protection solutions. Veeam has been active in acquisitions, joining a broader trend in the data protection market. Recently, Commvault acquired Clumio, Cohesity merged with Veritas, and Veeam itself bought Cirrus from CT4, which later became part of the Veeam Data Cloud. Earlier this year, Veeam also acquired Coveware, an incident response vendor. “Veeam hasn’t traditionally been an acquisition-heavy company, but that has changed in recent years,” said Rick Vanover, Veeam’s VP of product strategy. “I expect this trend to continue.” Alcion’s Role at Veeam This acquisition strengthens Veeam’s expertise in the fast-growing as-a-service market. Alcion’s team of fewer than 50 employees, including founders Niraj Tolia and Vaibhav Kamra, joins Veeam, with Tolia stepping in as Veeam’s new CTO. Tolia will lead product strategy and engineering for Veeam Data Cloud, succeeding Danny Allan, who recently became CTO at cybersecurity company Snyk. Alcion, which has hundreds of customers, will offer those customers the opportunity to transition to Veeam Data Cloud. However, Veeam has not finalized the future of Alcion’s product or established a timeline for its integration. “This acquisition brings incredible talent and thought leadership to Veeam, especially from Niraj and the Alcion team,” said Brandt Urban, Veeam’s senior VP of worldwide cloud sales. “Their expertise will help us rapidly enhance Veeam Data Cloud, adding more capabilities and expanding workload coverage.” Analysts, like Bertrand, expect Veeam to broaden its data protection offerings for additional SaaS platforms beyond Microsoft 365, looking toward collaboration and DevOps tools as potential areas for growth. AI and Security at the Forefront Alcion’s AI-powered features allow administrators to optimize backups, detect malware, and respond proactively to threats. According to Krista Case, an analyst at The Futurum Group, Alcion uses AI strategically to adapt backup schedules based on data modification patterns, trigger backups when potential threats are identified, and recommend the best recovery points. “When practitioners talk about cyber resilience, they’re focused on minimizing data loss and downtime—Alcion’s AI capabilities directly address these concerns,” said Case. Veeam has also been integrating AI into its existing products, offering inline malware detection and an Intelligent Diagnostics service. A forthcoming Copilot feature for Microsoft 365 backups will further enhance AI-driven data protection. Veeam Latest Acquisition “AI is a real asset when applied thoughtfully—it’s not just hype,” said Bertrand, adding that users are more interested in AI’s ability to drive outcomes, like detecting threats that could otherwise go unnoticed. Veeam executives echoed the importance of delivering clear, tangible AI benefits. “We keep user outcomes front and center because, otherwise, AI becomes an expensive experiment,” Vanover said. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 8, 2024in Data
Machine Learning on Kubernetes
05Sep

Machine Learning on Kubernetes

How and Why to Run Machine Learning Workloads on Kubernetes Running machine learning (ML) model development and deployment on Kubernetes has become essential for optimizing resources and managing costs. As AI and ML tools gain mainstream acceptance, business and IT professionals are increasingly familiar with these technologies. With the growing buzz around AI, engineering needs in ML and AI have expanded, particularly in managing the complexities and costs associated with these workloads. The Need for Kubernetes in ML As ML use cases become more complex, training models has become increasingly resource-intensive and costly. This has driven up demand and costs for GPUs, a key resource for ML tasks. Containerizing ML workloads offers a solution to these challenges by improving scalability, automation, and infrastructure efficiency. Kubernetes, a leading tool for container orchestration, is particularly effective for managing ML processes. By decoupling workloads into manageable containers, Kubernetes helps streamline ML operations and reduce costs. Understanding Kubernetes The evolution of engineering priorities has consistently focused on minimizing application footprints. From mainframes to modern servers and virtualization, the trend has been towards reducing operational overhead. Containers emerged as a solution to this trend, offering a way to isolate application stacks while maintaining performance. Initially, containers used Linux cgroups and namespaces, but their popularity surged with Docker. However, Docker containers had limitations in scaling and automatic recovery. Kubernetes was developed to address these issues. As an open-source orchestration platform, Kubernetes manages containerized workloads by ensuring containers are always running and properly scaled. Containers run inside resources called pods, which include everything needed to run the application. Kubernetes has also expanded its capabilities to orchestrate other resources like virtual machines. Running ML Workloads on Kubernetes ML systems demand significant computing power, including CPU, memory, and GPU resources. Traditionally, this required multiple servers, which was inefficient and costly. Kubernetes addresses this challenge by orchestrating containers and decoupling workloads, allowing multiple pods to run models simultaneously and share resources like CPU, memory, and GPU power. Using Kubernetes for ML can enhance practices such as: Challenges of ML on Kubernetes Despite its advantages, running ML workloads on Kubernetes comes with challenges: Key Tools for ML on Kubernetes Kubernetes requires specific tools to manage ML workloads effectively. These tools integrate with Kubernetes to address the unique needs of ML tasks: TensorFlow is another option, but it lacks the dedicated integration and optimization of Kubernetes-specific tools like Kubeflow. For those new to running ML workloads on Kubernetes, Kubeflow is often the best starting point. It is the most advanced and mature tool in terms of capabilities, ease of use, community support, and functionality. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 5, 2024in Salesforce
Salesforce Success Story
05Jul

Case Study: Google Cloud and Tableau Ecommerce Success

An industry leader in lifesciences research and ecommerce, is tasked with integrating recent acquisitions, standardizing processes, and improving marketing return-on-investment. Ecommerce company moves to the cloud and adopts Google Cloud and Tableau to improve sales and operational efficiency. Google Cloud and Tableau Ecommerce Success to the rescue. Industry: Lifesciences and Biotechnology Research Problem: Leadership requested help driving an improved culture of proactive decision-making, rather than reactive. Implemented : Our solution? Results: Salesforce offers customized solutions for the ecommerce industry, assisting companies in this field to provide outstanding customer experiences, optimize workflows, and spur growth and brand loyalty. Salesforce offers digital transformation technology for life sciences, ecommerce, and biotechnology research industries. If you are considering a Salesforce health and life sciences implementation, contact Tectonic today. Like2 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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July 5, 2023in Salesforce, Salesforce Commerce Cloud, Salesforce Health and Life Sciences Solutions, Salesforce Implementation Services, Salesforce Optimization, Salesforce Success Stories, Salesforce Tableau
Salesforce Success Story
18Feb

Case Study: Salesforce Innovation for Hospitality

Major hospitality management firm, moves to the cloud and adopts Google Cloud and Salesforce to improve operational insights and decision-making. Tectonic assisted them to move to the cloud and obtatin quicker, actionable insights with business intelligence. Salesforce Innovation for Hospitality.

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February 18, 2023in Google Analytics, Salesforce, Salesforce Development Services, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Salesforce Optimization, Salesforce Success Stories

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