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uber.com_engineering.rss.xml - sfeed_tests - sfeed tests and RSS and Atom files |
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uber.com_engineering.rss.xml (11233B) |
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1 <?xml version="1.0" encoding="utf-8" ?> |
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2 <rss version="2.0"> |
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3 <channel> |
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4 <title> |
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5 <![CDATA[Engineering | Uber Blog]]> |
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6 </title> |
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7 <link>https://www.uber.com</link> |
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8 <description> |
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9 <![CDATA[]]> |
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10 </description> |
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11 <lastBuildDate>Fri Jan 31 2025 10:04:42 GMT+0000 (Coordinated Univer… |
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12 <language>en</language> |
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13 <item> |
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14 <title> |
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15 <![CDATA[MySQL At Uber]]> |
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16 </title> |
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17 <link> |
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18 <![CDATA[https://www.uber.com/blog/mysql-at-uber/]]> |
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19 </link> |
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20 <pubDate> |
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21 <![CDATA[2025-01-30 14:00:00]]> |
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22 </pubDate> |
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23 <category> |
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24 <![CDATA[Backend]]> |
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25 </category> |
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26 <description> |
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27 <![CDATA[<p>How does Uber achieve 99.99% availability across 2,0… |
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28 ]]> |
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29 </description> |
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30 </item> |
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31 <item> |
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32 <title> |
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33 <![CDATA[How Uber Uses Ray® to Optimize the Rides Business]]> |
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34 </title> |
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35 <link> |
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36 <![CDATA[https://www.uber.com/blog/how-uber-uses-ray-to-optimize… |
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37 </link> |
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38 <pubDate> |
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39 <![CDATA[2025-01-09 14:00:00]]> |
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40 </pubDate> |
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41 <category> |
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42 <![CDATA[Backend]]> |
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43 </category> |
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44 <description> |
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45 <![CDATA[<p>Large-scale computation is a major back end and infr… |
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46 ]]> |
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47 </description> |
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48 </item> |
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49 <item> |
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50 <title> |
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51 <![CDATA[Serving Millions of Apache Pinot™ Queries with Neutri… |
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52 </title> |
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53 <link> |
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54 <![CDATA[https://www.uber.com/blog/serving-millions-of-apache-pi… |
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55 </link> |
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56 <pubDate> |
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57 <![CDATA[2024-12-11 14:00:00]]> |
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58 </pubDate> |
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59 <category> |
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60 <![CDATA[Data / ML]]> |
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61 </category> |
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62 <description> |
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63 <![CDATA[<p>At Uber, we serve 500 million Pinot queries every da… |
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64 ]]> |
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65 </description> |
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66 </item> |
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67 <item> |
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68 <title> |
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69 <![CDATA[Introducing the Prompt Engineering Toolkit]]> |
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70 </title> |
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71 <link> |
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72 <![CDATA[https://www.uber.com/blog/introducing-the-prompt-engine… |
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73 </link> |
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74 <pubDate> |
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75 <![CDATA[2024-11-26 14:00:00]]> |
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76 </pubDate> |
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77 <category> |
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78 <![CDATA[Data / ML]]> |
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79 </category> |
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80 <description> |
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81 <![CDATA[<p>LLM iteration can happen with speed and safety! Expl… |
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82 ]]> |
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83 </description> |
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84 </item> |
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85 <item> |
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86 <title> |
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87 <![CDATA[The Accounter: Scaling Operational Throughput on Uber�… |
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88 </title> |
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89 <link> |
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90 <![CDATA[https://www.uber.com/blog/the-accounter/]]> |
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91 </link> |
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92 <pubDate> |
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93 <![CDATA[2024-11-21 14:00:00]]> |
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94 </pubDate> |
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95 <category> |
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96 <![CDATA[Backend]]> |
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97 </category> |
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98 <description> |
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99 <![CDATA[<p>Uber slashed operational costs using The Accounter�… |
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100 ]]> |
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101 </description> |
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102 </item> |
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103 <item> |
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104 <title> |
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105 <![CDATA[Unified Checkout: Streamlining Uber’s Payment Ecosyst… |
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106 </title> |
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107 <link> |
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108 <![CDATA[https://www.uber.com/blog/unified-checkout/]]> |
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109 </link> |
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110 <pubDate> |
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111 <![CDATA[2024-11-14 14:00:00]]> |
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112 </pubDate> |
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113 <category> |
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114 <![CDATA[Backend]]> |
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115 </category> |
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116 <description> |
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117 <![CDATA[<p>From payment chaos to calm: Discover how Uber’… |
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118 ]]> |
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119 </description> |
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120 </item> |
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121 <item> |
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122 <title> |
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123 <![CDATA[Presto® Express: Speeding up Query Processing with Min… |
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124 </title> |
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125 <link> |
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126 <![CDATA[https://www.uber.com/blog/presto-express/]]> |
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127 </link> |
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128 <pubDate> |
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129 <![CDATA[2024-11-07 14:00:00]]> |
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130 </pubDate> |
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131 <category> |
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132 <![CDATA[Data / ML]]> |
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133 </category> |
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134 <description> |
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135 <![CDATA[<p>Slow Presto® queries can hinder data-driven operati… |
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136 ]]> |
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137 </description> |
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138 </item> |
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139 <item> |
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140 <title> |
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141 <![CDATA[Enabling Infinite Retention for Upsert Tables in Apache… |
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142 </title> |
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143 <link> |
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144 <![CDATA[https://www.uber.com/blog/enabling-infinite-retention-f… |
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145 </link> |
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146 <pubDate> |
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147 <![CDATA[2024-10-31 13:00:00]]> |
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148 </pubDate> |
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149 <category> |
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150 <![CDATA[Data / ML]]> |
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151 </category> |
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152 <description> |
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153 <![CDATA[<p>With contributions from Uber and others, Apache Pino… |
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154 ]]> |
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155 </description> |
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156 </item> |
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157 <item> |
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158 <title> |
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159 <![CDATA[Streamlining Financial Precision: Uber’s Advanced Set… |
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160 </title> |
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161 <link> |
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162 <![CDATA[https://www.uber.com/blog/ubers-advanced-settlement-acc… |
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163 </link> |
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164 <pubDate> |
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165 <![CDATA[2024-10-24 13:00:00]]> |
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166 </pubDate> |
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167 <category> |
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168 <![CDATA[Backend]]> |
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169 </category> |
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170 <description> |
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171 <![CDATA[<p>Discover how Uber’s cutting-edge settlement accoun… |
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172 ]]> |
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173 </description> |
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174 </item> |
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175 <item> |
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176 <title> |
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177 <![CDATA[Open Source and In-House: How Uber Optimizes LLM Traini… |
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178 </title> |
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179 <link> |
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180 <![CDATA[https://www.uber.com/blog/open-source-and-in-house-how-… |
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181 </link> |
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182 <pubDate> |
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183 <![CDATA[2024-10-17 15:30:00]]> |
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184 </pubDate> |
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185 <category> |
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186 <![CDATA[Engineering]]> |
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187 </category> |
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188 <description> |
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189 <![CDATA[<p>Exploring beyond third-party LLMs, Uber leverages in… |
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190 ]]> |
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191 </description> |
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192 </item> |
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193 <item> |
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194 <title> |
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195 <![CDATA[Genie: Uber’s Gen AI On-Call Copilot]]> |
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196 </title> |
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197 <link> |
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198 <![CDATA[https://www.uber.com/blog/genie-ubers-gen-ai-on-call-co… |
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199 </link> |
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200 <pubDate> |
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201 <![CDATA[2024-10-10 13:00:00]]> |
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202 </pubDate> |
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203 <category> |
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204 <![CDATA[Data / ML]]> |
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205 </category> |
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206 <description> |
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207 <![CDATA[<p>Explore how Uber is leveraging Genie, its Generative… |
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208 ]]> |
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209 </description> |
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210 </item> |
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211 <item> |
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212 <title> |
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213 <![CDATA[Making Uber’s ExperimentEvaluation Engine 100x Faster… |
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214 </title> |
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215 <link> |
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216 <![CDATA[https://www.uber.com/blog/making-ubers-experiment-evalu… |
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217 </link> |
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218 <pubDate> |
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219 <![CDATA[2024-10-03 13:00:00]]> |
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220 </pubDate> |
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221 <category> |
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222 <![CDATA[Backend]]> |
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223 </category> |
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224 <description> |
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225 <![CDATA[<p>Learn how Uber was able to reduce evaluation latenci… |
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226 ]]> |
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227 </description> |
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228 </item> |
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229 <item> |
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230 <title> |
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231 <![CDATA[Preon: Presto Query Analysis for Intelligent and Effici… |
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232 </title> |
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233 <link> |
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234 <![CDATA[https://www.uber.com/blog/preon/]]> |
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235 </link> |
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236 <pubDate> |
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237 <![CDATA[2024-09-26 13:00:00]]> |
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238 </pubDate> |
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239 <category> |
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240 <![CDATA[Data / ML]]> |
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241 </category> |
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242 <description> |
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243 <![CDATA[<p>Discover how to enable intelligent and efficient dat… |
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244 ]]> |
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245 </description> |
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246 </item> |
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247 <item> |
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248 <title> |
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249 <![CDATA[How to Measure Design System at Scale]]> |
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250 </title> |
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251 <link> |
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252 <![CDATA[https://www.uber.com/blog/design-system-at-scale/]]> |
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253 </link> |
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254 <pubDate> |
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255 <![CDATA[2024-09-24 13:00:00]]> |
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256 </pubDate> |
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257 <category> |
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258 <![CDATA[Engineering]]> |
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259 </category> |
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260 <description> |
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261 <![CDATA[<p>Learn how Uber made a breakthrough in tracking desig… |
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262 ]]> |
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263 </description> |
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264 </item> |
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265 <item> |
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266 <title> |
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267 <![CDATA[QueryGPT – Natural Language to SQL Using Generative A… |
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268 </title> |
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269 <link> |
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270 <![CDATA[https://www.uber.com/blog/query-gpt/]]> |
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271 </link> |
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272 <pubDate> |
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273 <![CDATA[2024-09-19 13:00:00]]> |
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274 </pubDate> |
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275 <category> |
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276 <![CDATA[Backend]]> |
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277 </category> |
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278 <description> |
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279 <![CDATA[<p>Discover how QueryGPT revolutionizes SQL query gener… |
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280 ]]> |
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281 </description> |
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282 </item> |
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283 <item> |
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284 <title> |
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285 <![CDATA[Transforming Executive Travel: Delegate Booking with Ub… |
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286 </title> |
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287 <link> |
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288 <![CDATA[https://www.uber.com/blog/executive-travel/]]> |
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289 </link> |
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290 <pubDate> |
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291 <![CDATA[2024-09-12 13:00:00]]> |
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292 </pubDate> |
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293 <category> |
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294 <![CDATA[Backend]]> |
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295 </category> |
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296 <description> |
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297 <![CDATA[<p>Find out how Uber for Business launched delegate pro… |
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298 ]]> |
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299 </description> |
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300 </item> |
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301 <item> |
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302 <title> |
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303 <![CDATA[DataMesh: How Uber laid the foundations for the data la… |
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304 </title> |
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305 <link> |
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306 <![CDATA[https://www.uber.com/blog/datamesh/]]> |
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307 </link> |
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308 <pubDate> |
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309 <![CDATA[2024-09-10 13:00:00]]> |
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310 </pubDate> |
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311 <category> |
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312 <![CDATA[Data / ML]]> |
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313 </category> |
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314 <description> |
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315 <![CDATA[<p>Learn how Uber is streamlining the Cloud migration o… |
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316 ]]> |
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317 </description> |
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318 </item> |
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319 </channel> |
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320 |
