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Tag: DevOps

  • Cybersixgill Significantly Streamlines Cyber Threat Reporting with Investigation Report Builder

    Tel Aviv, ISRAEL, September 13, 2023 – Cybersixgill, the global cyber threat intelligence data provider, introduced today its new Investigation Report Builder, an enhancement to its cyber threat intelligence (CTI) Investigative Portal designed to significantly ease the burden of reporting for threat and SOC analysts, threat hunters, and MSSPs.

    Available immediately, the Investigation Report Builder accelerates custom report creation, enabling users to generate, edit, duplicate, or delete reports quickly. The new feature enhances the efficiency and effectiveness of cybersecurity professionals through streamlined communication of investigation findings, insights, and recommendations to clients and stakeholders. It also helps MSSPs easily communicate risk and ROI to customers.

    “Reports of all kinds, ranging from strategic intelligence to operational intelligence reports, are invaluable to cyber threat intelligence practitioners. By harnessing the insights and analysis contained in these reports, practitioners can proactively defend their organization against cyber threats, strengthen its security posture, and safeguard critical assets from malicious actors,” said Gabi Reish, Chief Product Officer for Cybersixgill. “Our new Report Builder has transformed the process of creating CTI reports, streamlining and expediting their development while ensuring accuracy, consistency, and relevance.”

    Investigation Report Builder: A Painkiller for CTI Reporting

    Cybersixgill’s new Report Builder allows users to easily generate custom reports by collecting intelligence components from Cybersixgill’s Investigative Portal platform and organizing them in a report template without requiring manual input. Designed for greater efficiency and organization, the feature simplifies how threat analysts and MSSPs communicate investigation findings, insights, and recommendations and enables a broader understanding of the organization’s risk posture for multiple internal and external stakeholders.

    The Investigation Report Builder enables generation of a wide variety of CTI reports, including incident response reports, risk and compliance reports, executive-level communications, and third-party risk reports, among others.

    A video walk-through of Cybersixgill’s new Report Builder is available here.

    Key Takeaways:

    • New Report Builder solves the challenge of arduous and time-consuming threat intelligence report creation by providing drag-and-drop usability to quickly generate, edit, and duplicate reports.
    • New feature allows threat and SOC analysts to quickly share detailed reports of findings, insights, and recommendations to stakeholders, and gives MSSPs an easy way to share ROI and risk data with customers.
    • The Investigation Report Builder is immediately available for new and existing customers. More information is available here.

    About Cybersixgill
    Cybersixgill continuously collects and exposes the earliest indications of risk by threat actors moments after they surface on the clear, deep, and dark web. The company’s vast intelligence data lake, derived from millions of underground sources, is processed, correlated, and enriched using automation and advanced AI. Cybersixgill captures, processes, and alerts teams to emerging threats, TTPs, IOCs, and their exposure to risk based on each organization’s complete attack surface and internal context. Its expert intelligence and insights, available through a range of seamlessly integrated options, enable customers to pre-empt threats before they materialize into attacks. The company serves and partners with global enterprises, financial institutions, MSSPs, and government and law enforcement agencies. For more information, visit https://www.cybersixgill.com/ and follow us on Twitter and LinkedIn. To schedule a demo, please visit https://cybersixgill.com/book-a-demo.

  • How serverless services help M&E companies gain a strategic advantage in a competitive market

    How serverless services help M&E companies gain a strategic advantage in a competitive market

    The media and entertainment (M&E) industry has evolved with the digitization of content, proliferation of platforms, changes in the way media is consumed, emergence of user generated content, and globalization. These changes are fueled by and fuel consumer behavior and expectations. Those who were once happy to just record a live telecast of a show that they missed now expect instant access to any form of content they want, on any device. The market is fiercely competitive and consumers have a lot of choice, which makes it harder to acquire and retain audiences. In the US, the average churn rate across all paid streaming video-on-demand services has been at 37% since 2020 (Deloitte, 2022).

    To keep up, M&E companies need to create quality content, efficiently manage resources to meet unpredictable consumer demand, deliver personalized viewer experiences, and make sure their infrastructure is highly performant, secure, resilient and scalable – all while managing costs. Companies across broadcast, streaming, publishing, gaming, and music turn to Amazon Web Services (AWS) for compute, storage, networking, content processing, and delivery needs with an aim to shift the undifferentiated work of managing servers to the cloud.

    Adopting serverless

    M&E companies like have adopted AWS serverless solutions for their compute needs. Serverless simplifies the management and scaling of cloud applications by shifting the management of the underlying compute resources to AWS. Tasks such as server management, resource allocation, security patching, and instance scaling are handled on AWS so that development teams can focus on delivering personalized customer experiences using their programming language of choice, accelerate their time to production, and lower total cost of ownership (TCO). They pay for only what is used, and are able to focus valuable human resources on innovation versus operations.

    Popular serverless services for compute include AWS Lambda, a compute service that lets you run code without provisioning or managing servers, and AWS Fargate, a serverless by-default compute plane that works with Amazon Elastic Container Service (Amazon ECS), a fully managed container orchestration service that makes it easy to deploy, manage, and scale containerized applications.

    We’ve increasingly observed M&E companies embracing Event-Driven Architectures (EDA) to increase the resiliency and performance of their applications, improve agility to deploy features quickly, and optimize costs. EDA uses events and asynchronous communication to loosely couple an application’s components, providing flexibility and scalability to meet business demands. AWS offers many services, including Amazon EventBridge and AWS Step Functions, that can help organizations build EDAs, and together with AWS Lambda, and Amazon ECS with AWS Fargate, build powerful, real-time digital experiences at scale.

    Here’s how some M&E companies use serverless and EDA to meet their most demanding needs

    Meet spikes in consumer demand in real time: From the broadcast of live events to the premiere of a popular TV show, M&E companies often need to plan for higher-than-usual demand and spikes in workloads. AWS serverless services provide the scalability and flexibility to meet this demand without the need to provision and manage servers ahead of time. These services help M&E companies maintain consistent performance at peak and off-peak times as they can scale automatically when needed, without any manual configuration or dip in performance. For instance, with Amazon ECS, resources can automatically scale with the ability to launch millions of containers across availability zones in the cloud.

    This is why TV TOKYO, the broadcaster of one of the strongest lineups of business news in Tokyo, relaunched its business program on Amazon ECS with AWS Fargate. The subscription-based service needed new capabilities to deliver live broadcasts and VOD up to five times more quickly than the old system. The team made a strategic decision to use Amazon ECS with AWS Fargate to modernize its front-end infrastructure and make the service more scalable. This enabled automatic scaling  and reduced the risk of server downtime when demand spiked. In addition, TV TOKYO cut down the time needed to conduct technical preparation for live events like the House of Representatives’ general election from a month to a week, and even slash time spent responding to emergencies because of lower operational workload.

    Gain strategic advantage by reducing time to market: M&E companies are looking to build direct relationships with their end users and are quickly launching new services, especially over-the-top (OTT) streaming services, to offer audiences engaging content across platforms. Consumers have multiple options for instant viewing experiences, and with more choice comes more churn. While quality content helps acquire and retain audiences, companies need to invest time and resources in enhancing the viewing experience with high-quality video streaming, providing personalized interactions and communication, ensuring seamless integration across devices, and more. With services like AWS Lambda, companies benefit from automatic scaling, built-in high availability, and a pay-for-value bill model, without having to worry about infrastructure management tasks like capacity provisioning and security patching. Instead of managing and operating servers or runtimes, companies can release quickly, get feedback, and iterate to get to market faster, allowing them to compete in a crowded market.

    For this reason, Economia, one of the largest media houses in the Czech market, uses AWS Lambda as part of its serverless infrastructure. Economia started building all its new applications cloud-native, and used AWS Lambda across use cases to gain the agility, flexibility, and speed it was looking for. With this approach, the company was able to test new technologies and products in minutes and days, instead of months.

    Deliver the best consumer experience with minimum downtime: With high consumer and advertiser expectations in a very competitive market, providing perfect viewing and interactive experience across multiple platforms is table stakes for M&E companies today. With serverless, companies are better positioned to deliver and run highly performant applications that are available 24/7, and are resilient and secure.

    With AWS serverless services, you can delegate responsibilities towards driving well-architected outcomes for applications to AWS. You leverage AWS best practices and expertise on performance, scalability, availability, and security, and AWS takes on tasks such as server management, resource allocation, and scaling. AWS makes it easy to employ monitoring and observability tools within these services. Companies that require scale across regions use AWS Lambda for key back-end and front-end functions. It maintains compute capacity across multiple Availability Zones (AZs) in each AWS Region to help protect their code against individual machine or data center facility failures. Similarly, Amazon ECS with AWS Fargate has the ability to launch containers at scale across multiple availability zones, eliminating the risk of server downtime for customers, and allowing them to deploy globally, across multiple regions.

    To access some of these benefits, TiVo, a subsidiary of entertainment technology company Xperi Inc., builds its API stack with Amazon API Gateway, AWS Lambda and Amazon DynamoDB. Its technology stack allows the company to maintain a separation of concerns approach, and build lightweight APIs to query and respond predictably in client use cases. Amazon API Gateway provides the management for internal and external APIs, and the APIs are powered by AWS Lambda, which performs the reading and writing operations. The company uses Amazon DynamoDB as its NoSQL data persistence layer, which allows it to attain single-digit millisecond performance for client use cases. Using these serverless services, TiVo was able to modernize its stack, and improve scalability to stream globally and support hundreds of millions of calls per day.

    Reduce costs: With an eye on reducing production costs and protecting top-line revenues, many M&E companies are adopting AWS serverless services to help reduce TCO by reducing their infrastructure maintenance and development costs. Developers can optimize resource utilization so that they can focus on higher value tasks and never pay for over-provisioning with a pay-per-use billing model instead of provisioning infrastructure up front for peak capacity. Serverless and event-driven applications also reduce TCO by simplifying operations and reducing application management overhead to accelerate release cycles and increase performance. Customers can reduce their development time by 68% and reduce their TCO by up to 57% when they use AWS serverless solutions (Deloitte, 2021).

    A company that benefits from this is DAZN, with streaming broadcasts of top tier sports to millions of customers around the world. To deliver this experience, the company manages the deployment of complex video workflows while coordinating with backend application services that comprise its streaming platform. DAZN used AWS Step Functions to build a lightweight, modular, and extensible orchestrator to automate its live sports streaming events. With the flexibility of AWS Step Functions, DAZN could coordinate both synchronous and asynchronous tasks in a series of steps within a single state machine where cost is only incurred during state transitions. No expensive polling mechanism is required—and the system only moves on to the next step when it is ready. Automatically deploying workloads on the cloud right before an event starts allowed DAZN to optimize its costs and minimize operational overhead.

    Summary

    M&E companies are adopting AWS serverless services across several use cases to gain a strategic advantage in a competitive market. Instead of managing and operating servers or runtimes, companies can focus on product innovation, accelerate business value realization, enhance developer productivity, and control costs. M&E companies successfully use AWS serverless services to:

    • Automatically scale without manual configuration, allowing them to consistently meet demand during on-and-off peak events.
    • Shift the undifferentiated heavy-lifting of infrastructure provisioning and management to AWS, allowing developers to focus on writing code that creates business value quickly.
    • Deliver and run highly available, resilient, and secure applications that support global scale, reduce downtime, and deliver exceptional customer experiences.
    • Reduce TCO by allowing developers to optimize resource utilization so that they can focus on higher value tasks and never pay for over-provisioning with a pay-per-use billing model, and simplifying operations and reducing application management overhead to accelerate release cycles and increase performance.

    To learn more about AWS serverless services, visit https://aws.amazon.com/serverless/ and https://serverlessland.com/.

  • The Forrester Wave: Functions-As-A-Service Platforms, Q2 2023

    The Forrester Wave: Functions-As-A-Service Platforms, Q2 2023

    AWS Lambda named a leader in The Forrester Wave: Functions-As-A-Service Platforms, Q2 2023

    The Forrester Wave evaluation highlights Leaders, Strong Performers, Contenders, and Challengers. It’s an assessment of the top vendors in the market. Clients can view Forrester’s product evaluations and compare vendors, using the Excel-based comparison tool to influence their buying decisions for Functions-as-a-Service (FaaS).

    Read More

  • Containers and Serverless Recommendation Guide

    Containers and Serverless Recommendation Guide

    Unlock the power of modern application development. Accelerate innovation, enhance performance, fortify security, and boost reliability while significantly reducing your TCO.

    Which containers or serverless service should I start with to modernize my existing or build new applications?

    There are two primary operating models for building, running, and modernizing code on AWS: Kubernetes and Serverless. Many customers choose one or the other, and some use both depending on the application.

    Read More

  • Generative AI and Software Testing Tools to Manage Technical Debt

    Generative AI and Software Testing Tools to Manage Technical Debt

    It is easy to take a pessimistic view of generative AI and large language models (LLMs), especially when a growing list of AI experts and public figures have voiced concern about their potential to lead to dire consequences—even to human extinction. But we must also consider how these same technologies might mitigate these risks. There is no doubt that we are living in an accelerated cycle of technological progress and repercussions. However, the intelligence, speed and agility of AI—and particularly machine learning (ML)—may be just what we need to roll with the punches.

    As the speed of development outpaces our ability to mitigate potential risks posed by the systems we build, we are set on a path to accruing massive technical debt—the ever-increasing costs associated with modernizing code later rather than sooner. Too often, organizations in the private and public sectors are reluctant to pay off this debt, choosing an “if it ain’t broke, don’t fix it” mentality toward software maintenance and security. The problem is that as technology outgrows and outpaces our critical infrastructure systems, the potential for catastrophe escalates.

    Machine Learning: A Tool for the New “Space Race”

    Automated testing has proven superior in regression testing, especially in visually recognizing potential issues at the pixel level. If, for example, an important element of your interface is missing from the screen after an update, a visual test script can identify that faster than a human can. AI (and in particular, machine learning) generates test plans that provide more comprehensive coverage of the system under test and more practical coverage.

    Traditional testing methods usually begin with a broad and hypothetical analysis of user interactions. Test engineers begin by casting a wide net to cover the many possible user engagement scenarios they imagine. In contrast, AI-assisted systems learn from actual user interaction, building script libraries that focus on known points of weakness and vulnerability. It also does this at speed and scale. This technology is going to be essential to software test engineers as they inevitably find themselves unable to keep up with the abundance of code generated from LLMs using traditional testing methods.

    Technical Debt is Inevitable but not Unsolvable

    Every new iteration of software has the potential to introduce unforeseen problems ranging from glitchy bugs to catastrophic failures. The risks of releasing new software vary immensely between applications: It’s one thing if the latest release of your music streaming app crashes and quite another if the system that runs the regional power grid fails. One will result in unhappy customers; the other, the potential loss of life.

    The most critical systems (e.g., financial, transportation, safety, medical) are more likely to get frozen in time. Once a stable iteration is released, companies are generally not keen to make changes unless absolutely necessary—beginning the cycle of technical debt accumulation that grows until that debt is paid off by modernizing the code.

    Deciding when to pay off technical debt has always been a matter of weighing pros, cons, costs and benefits. But sometimes, such as in the case of an epic failure, that decision is forced. Both the risk of breaking the system and the cost of modernization compel developers to leave well enough alone. Meanwhile, the longer a system remains unchanged, the more isolated, outdated, and obsolete it becomes, setting the stage for failure.

    By introducing generative AI technology to the development stack along with other tools for authoring, compiling and testing software, developers will soon find themselves driving in the fast lane. With the security of knowing that code can be produced rapidly and released safely, owners of aging legacy systems will be more likely to modernize software sooner, helping them to pay off technical debt more quickly. That, in turn, could lead to increasingly rapid software development and release cycles, more work for developers, and more innovation. Such a workflow could very well become the embodiment of accelerating change, taking us from an “if it ain’t broke, don’t fix it” mentality to one where we anticipate the need for new code and avoid future catastrophic failures, or for that matter, human extinction.

  • Implement Object-Level Encryption and Policy With OpenTDF

    Implement Object-Level Encryption and Policy With OpenTDF

    With an exponential increase in data being generated, stored and shared online, the issue of data security no longer belongs to IT alone. Software and application developers have been put on notice along with business owners and legal teams worldwide to not only maintain data privacy but to build more secure products. There’s no easy solution. However, there are resources readily available for devs to build security into the fabric of their products. One is called OpenTDF, an open source project that lets you integrate encryption and data policy controls into your new and existing apps to safeguard your data, and the sharing of it, for you as well as your users.

    What’s TDF, and Why Should I Use OpenTDF?

    TDF, the “trusted data format,” was originally developed by the United States National Security Agency (NSA). It’s an open standard for object-level encryption that keeps data protected and under the data owner’s control, wherever it’s created or shared. TDF includes cryptographically secured metadata that ensures consistent policy control throughout the data life cycle. Picture this: You can grant, revoke or “turn off” data access at any time, even if the data has left your network or application.

    OpenTDF is an open source project that evolves the open TDF specification and provides a blueprint for getting started. There are a multitude of example applications that demonstrate the implementation logic, as well as streaming video and IoT use cases.

    The OpenTDF project is based on Kubernetes and OCI containers, and there is a quick start guide to get you up and running with a development environment. The quick start process will install supplemental services like Keycloak as well as project-specific services like key access service (KAS) and Abacus (an ABAC front end for configuration and management of attribute-based access control). Once you’ve completed a quick start installation, you’ll have a basic OpenTDF cluster with a Keycloak identity provider, PostgreSQL data store and a single entry point at localhost with an Nginx ingress controller.

    There’s an architectural diagram available on GitHub to see all of the services and service interactions.

    Several SDKs are available for building on the OpenTDF framework, including JavaScript, Python, C++ and Java. The client SDKs generally include basic examples for identity auth and creating a TDF-protected encrypted object.

    Take OpenTDF for a Spin: Secure Remote Storage

    Have you ever wondered how to make data access secure and simple? Using OpenTDF, developers can create that experience for their users. Let’s walk through a sample web application that uses OpenTDF to encrypt and upload data to cloud storage.

    The application we’ll be using is called OpenTDF Secure Remote Storage. It’s a react-based example that shows developers how to create encrypted data streams. These streams allow you to upload and download files from S3-compatible remote data stores while maintaining data protection. You can even remove encryption if needed.

    To make things easy, we’ll be using OpenTDF’s client-web SDK, which authenticates against Keycloak using OpenID Connect (OIDC). Keep in mind that this example runs on your local machine. It’s not designed for cloud or enterprise services.

    Prerequisites: You’ll need an S3-compatible storage object, like an Amazon S3 bucket. (You can create one for free here.)

    Set it Up

    First, install two CLI tools: Kind and Tilt. These will be used to deploy the OpenTDF services to your local machine. If you’re on macOS, you can install them with a simple Homebrew command: brew install kind tilt.

    Next, you will need the sample code on your local machine. You can either download the zip or clone the OpenTDF GitHub Repository using the following command: git clone git@github.com:opentdf/opentdf.git. This will create a directory called “opentdf” in your current location.

    Now, navigate to the root directory of the sample application: cd opentdf/examples/secure-remote-storage. To deploy OpenTDF, you’ll need a local Kubernetes cluster. Use the Kind CLI to create one: kind create cluster --name opentdf.

    Finally, start the application using Tilt: tilt up. This will launch the necessary OpenTDF services.

    Steps to Run the Application

    1. To begin, go to http://localhost:65432/secure-remote-storage in your web browser. This is where the Secure Remote Storage webpage is hosted.

    2. Now, it’s time to log in. Use the following credentials (defined in the bootstrap’s config file):
    ○ Username: user1
    ○ Password: testuser123

    3. Then, choose a file from your computer to upload. It can be anything – a text file, a PDF, or an image. Let your creativity flow! If you don’t have a file handy, no worries. You can download an image by right-clicking on it and selecting “Save As” from this link.

    4. Next, tell the application where to store your encrypted file. Provide the necessary JSON object that defines your S3-compatible object store. You can refer to the prerequisites for more details. (Optionally, you can save the configuration for future uploads. Just give it a name and click “Save.” This way, you won’t need to define the object store again in the future.)

    5. Now, it’s time to encrypt and upload. Click the “encrypt and upload” button, and watch the magic happen!

    What’s happening behind the scenes? When you click “encrypt and upload,” the application uses the OpenTDF API to convert your selected file into a .tdf file. It applies AES-GCM encryption and attaches access controls to ensure that only authorized users, like you (in this case, testuser123), can access the data. Even if your data store is public, your data remains secure.

    6. Ready to view and download your uploaded file? The table on the webpage lists all the files you’ve successfully uploaded. Each file has a download button next to it. Click that button, and the hosted file will be downloaded and decrypted on your local file system.

    Excited to explore more? Now that you’ve seen OpenTDF in action, you can dive into the source code of this application. Use this sample application as a starting point to integrate OpenTDF into your own secure applications.

    What Else is Possible With OpenTDF?

    From a secure webcam app to a privacy-forward menstrual tracking app and more, the possibilities are endless with OpenTDF and the future is in developers’ hands. By building on OpenTDF, the valuable data flowing through your applications will be protected forever.

    Learn more about OpenTDF at openTDF.io, and get the full quick-start guide, including more detailed instructions and other sample apps at the OpenTDF GitHub.

    Cassandra Zimmerman, technical product manager at Virtru, contributed to this article.

  • Grafana Demo


  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted to better serve our audience.

    Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

    Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

    The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

    We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

    CareerBuilder.com

    Cognizant Technology Solutions
    Phoenix, Arizona
    Senior DevOps Architect
    $130,000 to $180,000

    Indeed.com

    IBM
    Research Triangle Park, North Carolina
    SAP DevSecOps SME
    $126,000 to $235,000

    Dice.com

    DGN Technologies
    Dallas, Texas
    Azure DevOps Engineer
    $110,000 to $115,000

    SimplyHired.com

    Sabre Systems
    Lexington Park, Maryland
    Cloud Engineer – DevOps
    $106,000 to $134,000

    LinkedIn

    Deloitte
    Miami – Fort Lauderdale, Florida
    Junior Cloud Infrastructure Architect
    $65,000 to $97,000

  • Remembrance

    Remembrance

    Remembrance