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Software engineers, architects and team leads have found inspiration to drive change and innovation in their team by listening to the weekly InfoQ Podcast. They have received essential information that helped them validate their software development map. We have achieved that by interviewing some of the top CTOs, engineers and technology directors from companies like Uber, Netflix and more. Over 1,200,000 downloads in the last 3 years.

The InfoQ Podcast InfoQ

    • Technologie

Software engineers, architects and team leads have found inspiration to drive change and innovation in their team by listening to the weekly InfoQ Podcast. They have received essential information that helped them validate their software development map. We have achieved that by interviewing some of the top CTOs, engineers and technology directors from companies like Uber, Netflix and more. Over 1,200,000 downloads in the last 3 years.

    Gunnar Morling on Change Data Capture and Debezium

    Gunnar Morling on Change Data Capture and Debezium

    Today, on The InfoQ Podcast, Wes Reisz talks with Gunnar Morling. Gunnar is a software engineer at RedHat and leads the Debezium project. Debezium is an open-source distributed platform for change data capture (CDC). On the show, the two discuss the project and many of its use cases. Additionally, topics covered on the podcast include bootstrapping, configuration, challenges, debugging, and operational modes. The show wraps with long term strategic goals for the project.

    Why listen to this podcast:

    - CDC is a set of software design patterns used to react to changing data in a data store. Used for things like internal changelogs, integrations, replication, and event streaming, CDC can be implemented leveraging queries or against the DB transaction log. Debezium leverages the transaction log to implement CDC and is extremely performant.
    - Debezium has mature source and sink connectors for MySQL, SQL Server, and MongoDB. In addition, there are Incumbating connectors for Cassandra, Oracle, and DB2. Community sink connectors have been created for ElasticSearch.
    - In a standard deployment, Debezium leverages a Kafka cluster by deploying connectors into Kafka Connect. The connectors establish a connection to the source database and then write changes to a Kafka topic.
    - Debezium can be run in embedded mode. Embedded mode imports Java library into your own project and leverages callbacks for change events. The library approach allows Debezium implementations against other tools like AWS Kinesis or Azure's Event Hub. Going forward, there are plans to make a ready-made Debezium runtime.
    - Out of the box, Debezium has a one-to-one mapping between tables and Kafka topic queues. The default approach exposes the internal table structure to the outside. One approach to address exposing DB internals is to leverage the Outbox Pattern. The Outbox Pattern uses a separate outbox table as a source. Inserts into your normal business logic tables also make writes to the outbox. Change events are then published to Kafka from the outbox source table.

    More on this: Quick scan our curated show notes on InfoQ https://bit.ly/3737GZB
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    • 29 Min.
    Kelsey Hightower on Extending Kubernetes, Event-Driven Architecture, and Learning

    Kelsey Hightower on Extending Kubernetes, Event-Driven Architecture, and Learning

    In this podcast, Daniel Bryant sat down with Kelsey Hightower, Staff Developer Advocate at Google. Topics covered included: the extensibility of Kubernetes, and why it has become the platform that other platforms are being built on top of; creating event-driven architectures and deploying these onto Function-as-a-Service (FaaS) platforms like the Kubernetes-based Knative and Google Cloud Run; and the benefits of learning, sharing knowledge, and building communities.

    Why listen to this podcast:


    - Kubernetes is a platform for building platforms. It may not be as opinionated as traditional Platform-as-a-Service (PaaS) offerings, but it has become popular due to its extensibility. There are PaaS-like solutions built on top of Kubernetes, such as OpenShift, Knative, and Cloud Run.
    - The creation of common interfaces within Kubernetes -- such as Custom Resource Definitions (CRDs), Container Networking Interface (CNI), and Container Runtime Interface (CRI) -- enabled the adoption of the platform by vendors and the open source community without everyone needing to agree on exactly how to implement extensions.
    - Although not every workload can be effectively implemented using an event-driven architecture, for those that can the Kubernetes-based Function-as-a-Service (FaaS) platforms like Knative and Cloud Run can handle a lot of the operational management tasks for developers.
    - Engineers may be able to get ~90% of the “service mesh” traffic management functionality they need from using a simple proxy.
    However, the separation of the control and data planes within modern service meshes, in combination with the rise in popularity of the sidecar deployment model, has provided many benefits within Kubernetes.
    - A lot of learning within software development and information technology is transferable. If you spend time going deep in a technology when you begin your career, much of what you learn will be useful when you come to learn the next technology.

    More on this: Quick scan our curated show notes on InfoQ https://bit.ly/30alHC1
    You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

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    • 26 Min.
    Katie Gamanji on Condé Nast’s Kubernetes Platform, Self-Service, and the Federation and Cluster APIs

    Katie Gamanji on Condé Nast’s Kubernetes Platform, Self-Service, and the Federation and Cluster APIs

    In this podcast, Daniel Bryant sat down with Katie Gamanji, Cloud Platform Engineer at Condé Nast International. Topics covered included: exploring the architecture of the Condé Nast Kubernetes-based platform; the importance of enabling self-service deployment for developers; and how the Kubernetes’ Federation API and Cluster API may enable more opportunities for platform automation.

    - Founded in the early 1900s, Condé Nast is a global media company that has recently migrated their application deployment platforms from individually-curated geographically-based platforms, to a standardised distributed platform based on Kubernetes and AWS.
    - The Condé Nast engineering team create and manage their own Kubernetes clusters, currently using CoreOS’s/Red Hat’s Tectonic tool.
    Self-service deployment of applications is managed via Helm Charts. - The platform team works closely with their “customer” developer teams in order to ensure their requirements are being met.
    - The Kubernetes Federation API makes it easy to orchestrate the deployment of applications to multiple clusters. This works well for cookie-cutter style deployments that only require small configuration differences, such as scaling the number of running applications based on geographic traffic patterns.
    - The Cluster API is a Kubernetes project to bring declarative APIs to cluster creation, configuration, and management. This enables more effective automation for cluster lifecycle management, and may provide more opportunities for multi-cloud Kubernetes use.
    - The Condé Nast platform Kubernetes Ingress is handled by Traefik, due to the good Helm support and cloud integration (for example, AWS Route 53 and IAM rule synchronization). The platform team is exploring the use of service mesh for 2020.
    - Abstractions, interfaces, and security will be interesting focal points for improvement in the Kubernetes ecosystem in 2020.

    More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2FeYPrE
    You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

    Subscribe: www.youtube.com/infoq
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    Check the landing page on InfoQ: https://bit.ly/2FeYPrE

    • 31 Min.
    Joseph Jacks on Commercial Open Source Software, RISC-V, and Disrupting the Application Layer

    Joseph Jacks on Commercial Open Source Software, RISC-V, and Disrupting the Application Layer

    In this podcast, Daniel Bryant spoke to Joseph Jacks, Founder of OSS Capital and the Open Core Summit, and discussed topics including the open source and open core models, innovations within open source hardware and the RISC-V instruction set architecture, and current opportunities for disruption using commercial open source software.

    Why listen to this podcast:

    - Recently, open source software and the open core business model have driven a lot of innovation and created a lot of value, particularly within the cloud “as-a-service” space.
    - There has been some disagreement between the open source and commercially-focused communities, for example, in relation to the licencing models and how value is captured.
    - The Open Core Summit (OCS) is a new conference focusing on the intersection of commercialisation and open source software that aims to facilitate discussion in this space.
    - Organisations building around open source software can potentially look at large cloud vendors as partners. Public clouds can provide effective distribution, and typically focus on offering breadth of services rather than the depth of expertise that can be provided by a specialist company.
    - RISC-V is an open-source hardware instruction set architecture (ISA) based on the well-established reduced instruction set computer (RISC) principles. Leveraging RISC-V can reduce the time and cost of customising chip designs.
    - A lot of recent open source innovation has focused on the infrastructure layer within computing systems. This means that the application layer is now potentially ripe for disruption via commercial open source software.

    More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2rDfYYU
    You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

    Subscribe: www.youtube.com/infoq
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    Check the landing page on InfoQ: https://bit.ly/2rDfYYU

    • 26 Min.
    The InfoQ Podcast Hosts Take a Look Back at 2019, Discussing Teal, Edge, Quantum Computing, and more

    The InfoQ Podcast Hosts Take a Look Back at 2019, Discussing Teal, Edge, Quantum Computing, and more

    In this special year-end wrap-up podcast Wes Reisz, Shane Hastie, Daniel Bryant, and Charles Humble discuss what we’ve seen in 2019 and speculate a little on what we hope to see in 2020. Topics include business agility and Teal, what it means to be an ethical engineer, bringing your whole self to work, highlights from QCon and InfoQ during 2019, the rise of Python, and progress in quantum computing.

    Why listen to this podcast:

    * Business agility is one of the major themes that the InfoQ team has seen emerge this year, with stronger emphasis on outcomes over outputs. We’ve also seen a growing interest in ethics and the ethical implications of the work we all do.
    * On the programming languages front the rise of Python continues, driven largely by its popularity in data science.
    * As Kubernetes cements its dominant position we’re hoping to see a simplification of the workflows associated with it, as well as in areas like observability.
    * There have been several big announcements in quantum computing in the past year, and this is an area we continue to watch with interest.
    * Another key trend for next year is edge computing. The edge of the cloud infrastructure has an amazing amount of available compute resource, as does the device edge.

    More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2Z0Q9OI
    You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

    Subscribe: www.youtube.com/infoq
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    Check the landing page on InfoQ: https://bit.ly/2Z0Q9OI

    • 33 Min.
    Josh Wills on Building Resilient Data Engineering and Machine Learning Products at Slack

    Josh Wills on Building Resilient Data Engineering and Machine Learning Products at Slack

    Josh Wills, a software engineer working on data engineering problems at Slack, discusses the Slack data architecture and how they build and observe their pipelines. Josh, along with color commentary such as the move from IC to manager (and back), discusses recommendations, tips, tools, and lessons Slack engineering teams discovered while building products like Slack Search. The podcast covers machine learning, observability, data engineering, and general practices for building highly resilient software.

    Why listen to this podcast:

    - Slack has a philosophy of building only what they need. They have a don’t reinvent the wheel mindset.
    - Slack was originally a PHP monolith. Today, it is largely Hack-lang, HHVM, and several Java and Go binarys. On the data side, application logs are in Thrift (there is a plan to migrate to protobuf). Events are processed through a Kafka cluster that handles 100,000s of events per second. Everything is kept in S3 with a large Hive metastore. EMR is spun up on demand. Presto, Airflow, Slack, Snowflake (business analytics), Quiver (key value store) are all used.
    - ML worked best for Slack when it was used to help people answer questions. Things like Learn to Rank (LTR) become the most effective use of ML for Slack.
    - You can get pretty far with rules. Use machine learning when that’s all that’s left.
    - When you start applying observability to your data pipeline, a key lesson for Slack was to really focus on structured data, tracing, high cardinality events. This let them really use the tools they were already familiar with (ELK, Prometheus, Grafana) and go deep into understanding what’s happening in the systems.

    More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2PsVA4q
    You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

    Subscribe: www.youtube.com/infoq
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    Follow on LinkedIn: www.linkedin.com/company/infoq
    Check the landing page on InfoQ: https://bit.ly/2PsVA4q

    • 30 Min.

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