The platform allows customers to replicate data from on-premises to on-premises, cloud to cloud, on-premises to cloud, and cloud to on-premises. 

CData Sync Cloud provides integrations with over 300 data drivers, ranging from popular platforms like to smaller, more niche offerings that may be useful as well. Dynamics 365, NetSuite, Salesforce, ServiceNow, SharePoint, and Workday are some of the connections offered by CData.

Users are charged based on the number of data connections they use. This differs from the pricing model for other cloud ETL providers, which is usually volume-based, making it difficult to predict future costs. In those models, costs typically rise as data is replicated, CData explained.

“We are excited to bring our enterprise-grade ETL/ELT product, used by over 500 customers, to the cloud,” said Manish Patel, chief product officer of CData. “Because CData’s core focus is data connectivity, we are uniquely positioned to provide unmatched depth, breadth, and quality of connection with a supporting business model designed to scale with our customers’ usage – instead of punish them for it.”

Anthony Neu, senior manager of data analytics at Manhattan Associates, a customer of CData said: “Before migrating to CData Sync, I was burning through credits for data that I didn’t want or need. I got stressed with the volume pricing around what the units are and when are they used. It was very easy to make a mistake and, in turn, receive a large bill. We have something now that is very cost effective with CData.”

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DBOS (database oriented operating system) runs operating system services on top of high-performance distributed databases, creating a scalable, fault-tolerant, and cyber-resilient foundation for cloud-native applications with the added ability to store all state, logs, and other system data in SQL-accessible tables, the company explained.

Its first product offering is DBOS Cloud, which is a functions as a service (FaaS) platform that presents a significant advancement for developers looking to explore the capabilities of the DBOS operating system. As a transactional serverless application platform, DBOS Cloud facilitates the construction and operation of serverless functions, workflows, and applications. 

Its foundation on DBOS enables developers to tap into a framework designed for streamlined development processes and enhanced operational efficiency.

The platform’s integration with DBOS offers a distinctive user experience by simplifying the complexities traditionally associated with development, deployment, and operations. By leveraging DBOS Cloud, developers not only benefit from an environment that prioritizes ease of use but also gain advancements in cybersecurity and cyber-resilience. This dual focus ensures that applications built on DBOS Cloud are both robust against cyber threats and adaptable to the evolving digital landscape.

“The cybersecurity implications of DBOS are truly transformative,” said DBOS co-founder and former Head of Cybersecurity Practice at BCG Platinion, Michael Coden. “By simplifying the cloud application stack, DBOS greatly reduces the attack surface of cloud applications. On top of that, DBOS enables self-detection of cyberattacks within seconds without the use of expensive external analytics tools, and it can restore itself to a pre-attack state in minutes. It’s a DevSecOps game-changer.”

DBOS was co-founded by Mike Stonebaker, who created Postgres and won a Turing Award for his contributions “to the concepts and practices underlying modern database systems; Matei Zaharia, who was co-founder and CEO of Databricks; and a joint team of MIT and Stanford computer scientists. It was built based on several years of joint research from MIT and Stanford. 

“The cloud has outgrown 33 year-old Linux, and it’s time for a new approach,” said Stonebraker. “If you run the OS on a distributed database as DBOS does, fault-tolerance, multi-node scaling, state management, observability and security get much easier. You don’t need containers or orchestration layers, and you write less code because the OS is doing more for you.”

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Yet, this rise in API dominance brings with it a set of intricate challenges, particularly in management and security. Cloudflare’s ML algorithms detected 30.7% more API endpoints than what was self-reported by the organizations. According to the report, this gap underscores a worrying underestimation and potential vulnerability in API management. 

APIs that have not been managed or secured by the organization using it — also known as ‘Shadow’ APIs are often introduced by developers or individual users to run specific business functions,” the report stated. “While they are not inherently malicious, shadow APIs are essentially unprotected attack surfaces that introduce new risks. If exploited, shadow APIs can lead to data exposure, unpatched vulnerabilities, data compliance violations, lateral movement, and other threats.”

The report also found that over half (51.6%) of API error rates comprised “Too Many Requests” at 429 errors. This error speaks to rate-limiting concerns where the client has sent too many requests within a given timeframe, a mechanism web services use to control traffic and prevent abuse.

The 400 “Bad Request” error is next, making up 13.8% of the reported problems, often caused by sending data that the server cannot parse. The 404 “Not Found” and 401 “Unauthorized” errors follow closely, indicating that the requested resource is unavailable or the client lacks the necessary credentials to access it, according to the report. 

Best practices for security and management from the report start with the call for a unified approach that encompasses application development, visibility, performance, and security. This holistic perspective can be facilitated through a connectivity cloud, which acts as an intelligent platform connecting networks, cloud environments, applications, and users. Key aspects include automated API discovery for a comprehensive inventory of APIs, modern authentication and authorization processes, and endpoint management to monitor metrics like latency, errors, and response size.

Additionally, moving towards a “positive security” model is emphasized in the report, particularly through the use of an API gateway. This model operates on allowing only verified and known behaviors and identities, as defined by the API schema, and rejecting all others. This approach helps in effectively blocking malformed requests and HTTP anomalies which could lead to security breaches. Machine learning technologies are also recommended to aid in uncovering all API traffic, detecting attack variations, and differentiating between legitimate user traffic and potential malicious bot traffic.

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Building upon two decades of insights gained from millions of software, IT, and business teams, Atlassian announced in April its plans to integrate AI into teamwork experiences, showcasing the synergy between humans and AI.

The initial Atlassian Intelligence capabilities enhance individual productivity and tap into organizational data for immediate insights, simplifying data-driven decision-making. 

By leveraging AI, team members can draft business-critical content, automate routine tasks using natural language, summarize extensive content, and access context-specific help, fostering an environment where everyone can excel in their work with speed and efficiency, Atlassian explained.

For example, generative AI can now be used to instantly create user stories in Jira Software tickets and alter the tone of customer responses in Jira Service Management, and Confluence now offers AI-powered summaries and natural language automation.

Also in Confluence, the beta version of Q&A search enhances search results, allowing users to ask questions about project status, workflows, policies, or processes. The beta version of Q&A search in Compass streamlines information retrieval across microservices, systems, and teams by enabling users to ask questions in natural language about their technology stack, obtaining specific answers about components and deployments.

Atlassian Intelligence also enables teams to glean actionable insights from organizational data. Natural language interfaces can be used to write complex queries, providing flexible question-and-answer experiences across an organization’s knowledge base.

In addition, features like natural language to JQL and SQL, also available today, empower users to find issues and dependencies and access robust insights in Atlassian Analytics beyond data science teams.

According to Atlassian, the continual evolution of Atlassian Intelligence reflects its commitment to creating a future where humans and AI collaborate seamlessly to drive productivity and innovation in teamwork.

Atlassian, cloud, AIAdditional details are available here.

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With the growing shift towards the cloud, organizations are under pressure to scale rapidly, and JFrog’s integrations aim to address concerns about software supply chain security. The company emphasizes its commitment to innovation and investment in its global partner ecosystem.

The new JFrog Security within Jira Cloud allows JFrog security data to be integrated into Jira, making vulnerability management, application security, and compliance an integral part of developers’ workflows. It enhances collaboration and automation to ensure trusted releases at scale, and it is currently available in beta.

JFrog Workers, available in open beta for JFrog SaaS customers, offers a serverless execution environment for managing JFrog and third-party execution flows. It allows the creation and execution of custom scripts to further automate and connect developer workflows securely.

Other capabilities include PagerDuty Security Incident Alerts as part of the integration of JFrog Xray with PagerDuty, Datadog Log Analytics, and out-of-the-box log streaming for JFrog SaaS Customers to Datadog and Splunk, which will be available in open beta in Q4 ’23.

“The increasing complexity of today’s software ecosystems requires best-of-breed integrations between developer tools to help accelerate time to market without compromising security,” said Gal Marder, executive vice president of strategy at JFrog. “To truly protect your software supply chain you need to consider code both in development and in production at the binary level. I look forward to further collaborating with our partners on solutions and go-to-market strategies that provide significant value to our customers wanting to migrate and innovate securely in the cloud.”

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According to Immuta, having accurate metadata is important for data access control, monitoring, and regulatory compliance. Immuta Discover identifies structured data in cloud platforms and can use metadata from popular enterprise data catalogs, such as Alation, which is a data intelligence catalog. 

Immuta Discover is a key component of Immuta’s Data Security Platform, streamlining manual processes, enhancing data security, providing data visibility, and enabling organizations to unlock data value. This visibility of sensitive data aids can help companies create data protection policies and analyze data usage.

Immuta explained that effective data security relies on precise data discovery, tagging, and classification with detailed metadata. However, organizations face challenges due to the growing number of data sources and users. Existing solutions often lack accuracy and granularity, resulting in security vulnerabilities and compliance issues, according to Immuta in a post. 

The new tool addresses these challenges by enabling data teams to efficiently scan, classify, and tag data. This empowers organizations to implement data control policies and monitor data access, enhancing data security. Immuta offers over 60 pre-built classifiers, allowing organizations to customize data classifications to meet their specific needs and confidence levels.

“Immuta Discover is the foundational component to making any data security program work within your organization and to remain compliant,” said Mo Plassnig, chief product officer at Immuta. “It’s the first step that must happen in order to protect your data. Data is constantly changing in today’s digital age. Organizations must fully understand what data they have – with accurate classification – and maintain a trustworthy inventory of sensitive data across cloud platforms in order to meet growing data security and access demands. And Immuta Discover helps our customers accomplish just this.”

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It addresses the challenges of handling secrets and configuration at scale across various cloud environments. Pulumi ESC allows teams to gather secrets and configurations from multiple sources, and organize them into hierarchical collections called “environments.”

It then utilizes them across different infrastructure and application services. It can be used alongside Pulumi IaC for streamlined configuration management or independently to manage secrets and configuration for any project.

Pulumi ESC tackles common configuration and secrets management challenges with several key design principles by allowing users to define environments that contain secrets and configurations, offering integrations with secrets stored in various providers like AWS Secrets Manager, Vault, Azure OIDC, consume from anywhere capabilities, and much more. 

Pulumi ESC is available today in preview via the new esc CLI, as part of Pulumi Cloud, via the Pulumi Cloud REST API, and has direct integration with Pulumi IaC stack configuration and new pulumi env commands.

It also supports dynamically pulling secrets and configuration from other sources of truth, including AWS OIDC, AWS Secrets Manager, Azure OIDC, Azure KeyVault, Google Cloud OIDC, Google Secrets Manager, HashiCorp Vault, and Pulumi IaC Stack References – with many more sources like 1Password coming soon.

The creators of Pulumi ESC aim to add application-level SDKs, the ability to sync configuration to external systems, a dynamic configuration provider ecosystem, and versioning requirements in the coming months, according to this blog post.

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This innovative platform acts as a co-pilot for data teams, ensuring reliable, timely, and cost-effective data management in cloud data warehouses. It ultimately enables organizations to utilize data for crucial business decisions and leads to substantial cost savings, the company says.

“To make the most of your data and your budget, it’s critical to understand and address data quality, cost, performance and usage holistically,” said Shashank Gupta, CTO and co-founder of Revefi. “Revefi Data Operations Cloud provides for the right data at the right time at the right cost.”

Revefi Data Operations Cloud swiftly establishes connections between data quality, performance, spending, and usage without the need for manual setup. It utilizes proprietary AI models to create a baseline and continuously monitors for unexpected anomalies in spending or data usage. The system prioritizes issues by severity, provides information on the root causes, and empowers users to quickly address and resolve issues as they arise.

Revefi also announced that it has raised $10.5 million in a seed funding round.

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Prisma Cloud focuses on safeguarding the CI/CD environment and effectively shielding against potential open-source vulnerabilities using software composition analysis, according to the company in a blog post. 

“A major challenge in securing CI/CD pipelines is visibility. The myriad of third-party tools and applications running in development environments makes it almost impossible for security teams to determine if they are correctly configured,” said Ankur Shah, senior vice president of Prisma Cloud at Palo Alto Networks. “The integration of Cider’s capabilities secures the CI/CD environment and gives Prisma Cloud customers the ability to analyze individual tools, visualize how they interact with applications and each other, and identify and remediate risks.”

The CI/CD Security module empowers collaboration between DevOps and security teams, leading to enhanced security outcomes throughout the application life cycle, the company explained. 

When integrated into the existing Prisma Cloud platform, which comprises features such as Secrets Scanning, Software Composition Analysis, and Infrastructure as Code Security, it allows organizations to bolster security and risk prevention across the entire software delivery pipeline. 

According to Palo Alto Networks, this integration facilitates a comprehensive and holistic security approach that surpasses the capabilities of individual, isolated solutions.

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It can be compiled into Terraform/IaC and JavaScript, allowing for versatile usage. In Winglang, infrastructure resources hold a prominent position, being treated as first-class citizens.

One of the notable features of Winglang is its ability to automatically generate IAM policies and handle various cloud mechanics seamlessly.

Users can maintain their creative flow with minimal context switching and receive immediate feedback as well as have the capability to run their cloud applications in their local environments. They can also write unit tests for complete cloud architectures ensuring the quality and robustness of their code.

The tool provides visualization, interaction, and debugging functionalities locally, enabling users to have a comprehensive understanding and control of their applications.

Users have the flexibility to utilize any cloud service and compile their code to multiple cloud providers and provisioning engines while maintaining complete control over their infrastructure configuration and deployment. To ensure maximum portability, the tool provides a cloud-agnostic SDK that allows users to seamlessly work across different cloud environments.

Additional details are available here.

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