Welcome!


Top Stories

http://twitter.com/fuatkircaali The round of applause that greeted the suggestion that Ken Cron be promoted from Interim CEO to full CEO of Computer Associates International (renamed as CA as one of the first action items by John Swainson) left a smile on the face of Chairman Lewis Ranieri at the company's annual shareholder meeting in 2004. Ken had one of the toughest jobs any CEO can imagine: that of following Sanjay Kumar and Charles Wang. Yet under Cron's leadership CA's net income returned to the black after three consecutive years of losses and under very difficult circumstances. Of course later the full time job went to John Swainson, IBM's WebSphere chief, who announced his retirement from his post at the end of 2009 and at the age of 52. The Canadian press of course applauds Swainson as having been the savior of CA. I had a breakfast meeting with Ken not t... (more)

Facebook, Google, and the Near-Term Future of the USA

On the day when the Dow Jones Industrial Average topped 12,000 for the first time since June 2008, it was impossible not to correlate the eloquence and optimism of President Obama's "State of the Union" speech on Tuesday night with the restoration of a sense of perspective and hope in the USA about the future. Obama grasped the nettle full-on. "We are poised for progress," he declared, adding: "Two years after the worst recession most of us have ever known, the stock market has come roaring back. Corporate profits are up. The economy is growing." As one blogger expressed it, though - and he is a former Goldman Sachs trader called Tyler Durden, so he ought to know wheref he speaks: "There was a massive pink elephant in the room called reality though." Durden's gripe is with what he deems to be the unreality of Obama's praising Google and Facebook so highly in an Ameri... (more)

Design Patterns Were Not Born Equal

Design patterns were not born equal. Some of them are boring, while others are special. Do you remember your feelings after learning what the Data Transfer Object is? Don’t remember? Of course – cause you didn’t have any special feelings about it other than “It’s easy”. What do you say about Singleton? Yeah, this is kinda interesting pattern which gave you something to talk about. Do we really need it? Can’t we just achieve the same effect with static variables? Does it make your entire application tightly coupled? Lots to discuss and share your opinion in online forums. How about Visitor? You must have remembered those feelings when you ran into it first time. The day when you understood how the Visitor pattern works was crucial in your career – that was the moment when you realized that you were not junior software developer anymore. From that very moment you can ... (more)

Big Data Top Ten | @CloudExpo [#BigData]

What do you get when you combine Big Data technologies….like Pig and Hive? A flying pig? No, you get a “Logical Data Warehouse”. My general prediction is that Cloudera and Hortonworks are both aggressively moving to fulfilling a vision which looks a lot like Gartner’s “Logical Data Warehouse”….namely, “the next-generation data warehouse that improves agility, enables innovation and responds more efficiently to changing business requirements.” In 2012, Infochimps (now CSC) leveraged its early use of stream processing, NoSQLs, and Hadoop to create a design pattern which combined real-time, ad-hoc, and batch analytics. This concept of combining the best-in-breed Big Data technologies will continue to advance across the industry until the entire legacy (and proprietary) data infrastructure stack will be replaced with a new (and open) one. As this is happening, I predi... (more)

Operational Hadoop for Streaming Data By @MapR | @CloudExpo [#BigData]

Operational Hadoop and the Lambda Architecture for Streaming Data Apache Hadoop is emerging as a distributed platform for handling large and fast incoming streams of data. Predictive maintenance, supply chain optimization, and Internet-of-Things analysis are examples where Hadoop provides the scalable storage, processing, and analytics platform to gain meaningful insights from granular data that is typically only valuable from a large-scale, aggregate view. One architecture useful for capturing and analyzing streaming data is the Lambda Architecture, representing a model of how to analyze real-time and historical data together. In his session at Big Data Expo, Dale Kim, Director of Industry Solutions at MapR, will cover the practice of capturing canonical data "as it lands" as a baseline for accommodating future analytics requirements. Dale Kim is the latest author... (more)

Apache Drill’s Self-Service Capabilities By @MapR | @CloudExpo [#BigData]

Help Yourself: Leveraging Apache Drill's Self-Service Capabilities Small data management solutions don't work in our brave new Big Data world. Back in the small data days, we talked proudly about having gigabytes of structured data that had been carefully denormalized to reduce latency as much as possible. Today's data is measured in petabytes, and it is dynamic, complex, and wildly varied in structure. Small data was a nicely planned garden, but Big Data is a jungle: rich with resources, abundant in growth, but also a bit overwhelming and easy to get lost in. Exploring that jungle requires solutions that enable interactive, self-service ways to work with historical as well as near real-time data. Hadoop and NoSQL on Hadoop solved a significant amount of Big Data access and availability problems. Add Apache Drill and SQL-on-Hadoop to the mix and you have a solution... (more)

Solr Redis Plugin Use Cases By @Sematext | @DevOpsSummit [#DevOps]

Solr Redis Plugin Use Cases and Performance Tests The Solr Redis Plugin is an extension for Solr that provides a query parser that uses data stored in Redis. It is open-sourced on Github by Sematext. This tool is basically a QParserPlugin that establishes a connection to Redis and takes data stored in SET, ZRANGE and other Redis data structures in order to build a query. Data fetched from Redis is used in RedisQParser and is responsible for building a query. Moreover, this plugin provides a highlighter extension which can be used to highlight parts of aliased Solr Redis queries (this will be described in a future). Use Case: Social Network Imagine you have a social network and you want to implement a search solution that can search things like: events, interests, photos, and all your friends' events, interests, and photos. A naive, Solr-only-based implementation wou... (more)

Announcing the @PagerDuty and @Dynatrace Integration | @DevOpsSummit [#DevOps]

Proactively Manage Application Performance with PagerDuty & Dynatrace We’re excited to announce a new integration with Dynatrace, a class-leading Application Performance Management (APM) solution. With Dynatrace’s PagerDuty plug-in, you can be notified about incidents when they occur. This enables a proactive APM experience and further reduced MTTR. How it Works Dynatrace monitors your entire application delivery chain. All of your transactions are tracked end-to-end, from user clicks to individual lines of code, using Dynatrace PurePath technology. Dynatrace constantly monitors your servers’ host and process health, and will automatically notify you if your business-critical transactions are running slower than normal with automatic baselines. Dynatrace comes with several incidents configured out of the box, but you can also create custom incidents to get as granula... (more)

Kafka 0.8.2 Monitoring Support By @Sematext | @DevOpsSummit [#DevOps]

Kafka 0.8.2 Monitoring Support SPM Performance Monitoring is the first Apache Kafka monitoring tool to support Kafka 0.8.2.  Here are all the details: Shiny, New Kafka Metrics Kafka 0.8.2 has a pile of new metrics for all three main Kafka components: Producers, Brokers, and Consumers.  Not only does it have a lot of new metrics, the whole metrics part of Kafka has been redone — we worked closely with Kafka developers for several weeks to bring order and structure to all Kafka metrics and make them easy to collect, parse and interpret. We could list all the Kafka metrics you can get via SPM, but in short — SPM monitors all Kafka metrics and, as with all things SPM monitors, all these metrics are nicely graphed and are filterable by server name, topic, partition, and everything else that makes sense in Kafka deployments. 103 Kafka metrics: Broker: 43 metrics Producer:... (more)

A DevOps Interview Series By @VictorOps | @DevOpsSummit [#DevOps]

What’s Planned for 2015? A DevOps Interview Series By Jason Hand I’m not one for lofty or overly-ambitious New Year’s resolutions, but I do feel that the beginning of the year is an excellent time to set  goals and make some changes in the name of continuous improvement. A personal goal I set for myself this year was to do better about staying in touch with friends and family. Often times I feel like I rely on social media to fill me in on what everyone who is important to me is up to. While social media is great and I love seeing pictures and reading about everyone’s personal and professional adventures, it lacks a true emotional and personal connection that only comes from spending quality time with each other, communicating directly with one another . I’ve decided that this effort should be extended beyond my own family and personal friends. Over the next severa... (more)

Chef Recipes By @ScripRock | @DevOpsSummit [#DevOps #Containers #GuardRail]

Generating Chef Recipes from Existing Configs We've covered the benefits and pitfalls of configuration management tools like Chef in many articles. But let's assume you've done your homework and decided Chef is the tool for you. How do you get started? Funnily enough, one of the inspirations for ScriptRock was a not-so-successful Chef deployment. Only a poor craftsman blames his tools, so rather than pointing the finger at Chef we reflected on what we had done wrong. The problems we encountered trying to move a large, brown-field infrastructure to Chef, and to get culture, people, and processes to change at the same time, drove us to find a sound method for enterprise automation. Essentially, we had put the cart before the horse: we started automating our infrastructure before we understood it. Without documentation of existing configuration state and scalable valida... (more)

IoT & Smart Cities Stories
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-c...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...