Amit Banerjee

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Amit Banerjee

Amit Banerjee

@banerjeeamit

Husband | Dad | Author | Engineering Leader at @Salesforce | (he/him) | ex-MSFT | Tweets r my opinions

Seattle Katılım Eylül 2009
859 Takip Edilen2.2K Takipçiler
Ophir Gottlieb
Ophir Gottlieb@OphirGottlieb·
Jut remember that the service reps at @CharlesSchwab / ToS are not responsible for the outage. Go easy on them. They are experiencing this like you are but with 15 million accounts.
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Andy Jassy
Andy Jassy@ajassy·
When we started AWS, we looked at the undesirable situation of developers spending 70% of their time on the undifferentiated muck of managing infrastructure (vs only 30% on what differentiated their customer experiences) and aimed to flip that equation on its head. It’s made a pretty big difference in innovation and developer productivity. Roughly 18 years later, we’re trying to solve another 70-30-like misalignment for developers, where developers are telling us that they’re spending roughly 70% of their time on repetitive and tedious tasks and code. Today, we’re launching the general availability of Amazon Q, the world’s most capable GenAI-powered assistant for accelerating software development and leveraging companies’ internal data—and that aims to remove much of the muck of repetitive and tedious coding and data tasks for developers and employees at large. On the software development side, Q doesn’t just generate code, it also tests code, debugs coding conflicts, and transforms code from one form to another (today, developers can save months using Q to move from older versions of Java to newer, more secure and capable ones; in the near future, Q will help developers transform their .net code as well). Q Agents does multi-step planning and reasoning to allow developers to string together multiple requests and have Q implement them. On the internal data side, most companies have voluminous troves of internally relevant data that resides in wikis, intranet pages, Salesforce, storage repositories like Amazon S3, and a bevy of other data stores and SaaS apps that are hard to access. It makes answering straightforward questions about company policies, products, business results, code, people, and many other topics hard and frustrating. Q makes this much simpler. You can point Q at all of your enterprise data repositories, and it’ll search all this data, summarize logically, analyze trends, and engage in dialog with customers about it. We also introduced today a powerful new capability called Q Apps, which lets employees describe, in natural language, what apps they want to build on top of this internal data, and Q Apps will quickly generate that app. This is going to make it *so* much easier for internal teams to build useful apps from their own data. Customers are gravitating to Q, and we already see companies like Brightcove, British Telecom, Datadog, GitLab, GoDaddy, National Australia Bank, NCS, Netsmart, Slalom, Smartsheet, Sun Life, Tata Consultancy Services, Toyota, and Wiz using Q. And, we’ve only been in beta til today. Very excited about how Q will change what’s possible for our customers, and being a part of helping them innovate more quickly. aboutamazon.com/news/aws/amazo…
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Marc Benioff
Marc Benioff@Benioff·
Meet the new Salesforce Einstein1 Copilot! 🚀 Just chat with it, and it'll help with meeting prep, landing pages, product catalogs, code, and more. Tailored for every industry. Fully customizable with clicks. Einstein Trust Layer built-in. Einstein Copilot activates your trusted company data and workflows to multiply every employee's productivity safely and securely. What's your favorite thing Einstein Copilot can do? ☁️🪄✨
Marc Benioff tweet media
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Amit Banerjee
Amit Banerjee@banerjeeamit·
In my line of work, I use spreadsheets a lot which have complex formulas. As time goes by the memory fails on why some of these complex formulas are created. Now you can use #ChatGPT or #Bing Chat to explain the spreadsheet formula to you and also create documentation for it!
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Amit Banerjee
Amit Banerjee@banerjeeamit·
@tjaybelt My preference in this space always has been to use an existing PaaS/SaaS offering if possible. If not, then look at building your solution first and avoid anything that logs to a store with ACID and WAL semantics. #sqlhelp
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TJay Belt
TJay Belt@tjaybelt·
#sqlhelp looking for ideas on logging application goings on. Folks want to drop it in a db. I'm betting there are better storage solutions for this non relational data, detailing the goings on of an application, and better suited for consumption. What are your faves?
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Amit Banerjee
Amit Banerjee@banerjeeamit·
@tjaybelt Or you could pick Splunk for a hybrid option which allows you to put the data into Splunk in an on-prem deployment or in Splunk cloud. #sqlhelp
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Amit Banerjee
Amit Banerjee@banerjeeamit·
@tjaybelt You could also use corleated tracing and build it in-house using Zipkin, OpenTracing, Jaeger, etc and put the data into a key-value store like MongoDB or a cloud store like DynamoDB or CosmosDB #sqlhelp
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Amit Banerjee
Amit Banerjee@banerjeeamit·
@tjaybelt You have a lot of options. There are cloud solutions like AppInsights, DataDog, and the likes #sqlhelp
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